Digital Commons Network^™

Generating Real-World Evidence In Early Alzheimer's Disease: Considerations For Applying The Target Trial Emulation Framework To Study The Safety Of Anti-Amyloid Therapies, Xiaojuan Li, Sonal Singh, Bahareh Rasouli, Jennifer Lyons, Noelle M. Cocoros, Richard Platt, Ivan Abi-Elias, Jerry H. Gurwitz

Department of Medicine Faculty Publications

Anti-amyloid beta monoclonal antibodies (anti-Aβ mAbs) have received approval from the US Food and Drug Administration for the treatment of patients with mild cognitive impairment or mild dementia due to Alzheimer's disease (collectively known as early AD) based on evidence from clinical trials. However, whether findings from these trials are generalizable to the real world is uncertain. We need reliable evidence on the real-world safety of these treatments to inform decision making for clinicians, patients, and caregivers. Using lecanemab as an exemplar, we outline the key considerations in designing and implementing an observational study on safety and utilization outcomes using …

Pediatric Cancer Incidence, Temporal Trends, And Mortality In The United States By Health Disparities Indicators, Seer (1973-2014), Prachi P. Chavan, Laurens Holmes Jr.

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Pediatric cancer incidence has been increasing in the United States, despite improvement in pediatric cancer survival. This steady increase in incidence trends is not completely understood but maybe associated with social and environmental factors. In this study we aimed to assess the cumulative incidence, temporal trends, and mortality rates in pediatric cancer. Additionally, we examined sub-group variability in both incidence and mortality rates. Methods: Data from Surveillance, Epidemiology, and End Results (SEER) −18 from 1973–2014 were used for the purpose of analysis in this study. Age-adjusted incidence rates were used to assess temporal trends in cancer among children aged < 1–19 years. Univariable and multivariable binomial regression models were used to examine the association between race and cancer mortality while adjusting for potential confounders. Results: There were 92,594 cancer diagnoses during this period. White children comprised 74,758, (80.7%), black children 10,030, (10.8%), and other races 6648, (7.2%). Overall the age-adjusted cumulative incidence was slightly higher among white children (16.4%) than black children (12.4%) and other (13.0%). Children aged 15–19 years and those in metropolitan regions were more likely to be diagnosed with pediatric cancer. Relative to females, males were 16% more likely to die from the disease [adjusted Risk Ratio (aRR): 1.16, 95% Confidence Interval (CI): 1.09–1.22]. Additionally, compared to white children, black children had higher mortality rates [(aRR): 1.37, 99% CI: 1.23–1.52]. Conclusions: There is an increasing trend in pediatric cancer incidence; while white children have the highest incidence, black children and males indicated a survival disadvantage, indicative of racial and sex variability in overall pediatric cancer in the United States.

Evaluating Spatiotemporal Vegetation Index Variation To Detect Salt Marsh Dieback On The Georgia Coast, Emmanuella Bosompemaa Obeng

College of Graduate Studies: Theses & Dissertations

Salt marshes, essential for coastal protection and carbon sequestration, are increasingly vulnerable to dieback events, threatening ecosystem resilience and vital services. Detecting these shifts early is essential for timely intervention. However, few studies have applied Early Warning Signals (EWS) to coastal marsh systems. Most EWS research has focused on lakes, forests, or climate tipping points, with limited application to salt marsh dieback in the southeastern U.S. Site-specific, long-term spatial analyses are also lacking, as prior work often examines short time frames or single disturbance events. This study investigates the spatiotemporal patterns of salt marsh dieback on the Georgia coast from …

A Hybrid Method For Source Direction Finding With Radio Frequency Interference And Gaussian White Noise, Yanming Zhang, Wenchao Xu, Antonios Argyriou, A. Long Jin, Tianquan Tang, Peifeng Ma, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a hybrid data-driven method, termed moving average-Hankel-dynamic mode decomposition (MAHankDMD), for joint direction of arrival (DOA) and frequency estimation in environments affected by both radio frequency interference (RFI) and Gaussian white noise. The proposed approach integrates two key components: (1) a moving average-DMD filter that effectively mitigates Gaussian white noise and separates RFI from the source signal, and (2) a Hankel-DMD method that accurately estimates the DOA of the filtered signal and associates it with the corresponding frequency. The moving average-DMD stage first enhances the signal-to-noise ratio and improves the robustness of the estimation process through noise …

Genai’S Impact On Global It Management: A Multi-Expert Perspective And Research Agenda, Yogesh K. Dwivedi, Laurie Hughes, Mohammad S. Al-Ahmadi, Vincent Dutot, Syed Q. Ahmed, Shahriar Akter, Rahul De’, Keyao Li, Nitish Singh, Paul Walton

Research outputs 2022 to 2026

Generative AI (GenAI) is disrupting global IT management and challenging established practice. The increasing use of GenAI technology is redefining localization, transforming existing workforce roles, outsourcing strategy, and team dynamics. Simultaneously, GenAI’s security complexities have prompted the rethinking of existing risk frameworks to meet a new set of challenges from GenAI enhanced cyber threats. This article explores these complex and converging factors, providing a roadmap to address GenAI’s significant impact on global IT management. We advocate the responsible adoption of GenAI and importance of building resilient, value-driven, globally consistent IT ecosystems able to adapt to the significant challenges and opportunities …

Extreme Value Theory Analysis Of High Emitter Trends Across Four Us Cities From 1995 To 2021, M. Matti Maricq, Gary A. Bishop

Fuel Efficiency Automobile Test Publications

Extreme value theory provides a direct means to characterize the distribution of high emitters within a vehicle fleet and calculate statistical confidence intervals for comparisons. Defining a “high emitter” as the maximum emitter in a random sample of N vehicles implies in the limit of large N that high emitters follow an extreme value distribution, comprised of three distinct domains. The analysis of over twenty years of roadside remote sensing emissions measurements in Chicago, Denver, Los Angeles and Tulsa reveals clear differences between gasoline vehicle high emitter distributions across pollutants (hydrocarbons (HC), carbon monoxide (CO) and nitric oxide (NO)), but …

Carbon Sequestration Through Conservation Tillage In Sandy Soils Of Arid And Semi-Arid Climates: A Meta-Analysis, Samantha Lynn Colunga, Leila Wahab, Alejandro Fierro-Cabo, Engil Isadora Pujol Pereira

School of Earth, Environmental, & Marine Sciences Faculty Publications

Highlights

• Under CST, SOC increased by 12.74 ± 1.46 % in sandy soils with 5 of the 6 practices contributing to this rise.
• SOC increased up to 15 years post-CST conversion, but more research is needed to assess long-term effects.
• SOC increased by 13% in soils with over 56% sand content under CST.
• SOC increased by 15% in the 0-20 cm depth under CST, with no significant increase at greater depths.
• SOC increased under CST when nitrogen was applied at rates up to 100 kg N ha⁻¹.

Abstract

This meta-analysis assessed soil organic carbon (SOC) percent changes in sandy soils, …

Reindsplit: Reinforced Dynamic Split Learning For Pest Recognition In Precision Agriculture, Vishesh Kumar Tanwar, Soumik Sarkar, Asheesh K. Singh, Sajal K. Das

Computer Science Faculty Research & Creative Works

To empower precision agriculture through distributed machine learning (DML), split learning (SL) has emerged as a promising paradigm, partitioning deep neural networks (DNNs) between edge devices and servers to reduce computational burdens and preserve data privacy. However, conventional SL frameworks' one-split-fits-all strategy is a critical limitation in agricultural ecosystems where edge insect monitoring devices exhibit vast heterogeneity in computational power, energy constraints, and connectivity. This leads to straggler bottlenecks, inefficient resource utilization, and compromised model performance. Bridging this gap, we introduce ReinDSplit, a novel reinforcement learning (RL)-driven framework that dynamically tailors DNN split points for each device, optimizing efficiency without …

Annual Diversity Of Honey Bee Pollen Sources In Two Pumpkin Growing Landscapes, Machakos County, Kenya, Marystella W. Nang’Oni, Muo Kasina, Rebecca Karanja, Mary M. Guantai, Rahab N. Kinyanjui, Evanson R. Omuse, Michael H.G. Lattorff, Elfatih M. Abdel-Rahman, Marian Adan, Samira A. Mohamed, Thomas Dubois

All Peer-Reviewed Publications

Multi-floral foraging sources for honey bee (Apis mellifera L.) have been threatened by landscape changes and unsustainable farming practices. In East Africa, the biodiversity of forage resources that could support honey bees, especially in agricultural lands, remains least explored. This study investigated pollen diversity for honey bees in Yatta and Masinga Sub-counties in Machakos County, Kenya. Honey bee hives were installed on eight pumpkin (Cucurbita maxima Duchesne ex Lam) farms (one hive per farm) in two varying landscape vegetation classes (low and medium) based on normalized difference vegetation index (NDVI). Pollen traps were installed at the hive entrance and pollen …

Governing Intelligence: Singapore’S Evolving Ai Governance Framework, Jason G. Allen, Jane Loo, Jose Luna

Research Collection Yong Pung How School Of Law

This paper provides an outline analysis of the evolving governance framework for Artificial Intelligence (AI) in Singapore. Across the Singapore government, AI solutions are being adopted in line with Singapore’s “Smart Nation Initiative” to leverage technology to make impactful changes to the nation and the economy. In tandem, Singaporean authorities have been assiduous to release a growing number of governance documents, which we analyse together to chart the city-state’s approach to AI governance in international comparison. Characteristics of Singapore’s AI governance approach include an emphasis on consensusbuilding between stakeholders (particularly government and industry but also citizens) andvoluntary or “quasi” regulation, …

An Exploratory Attempt To Incorporate Social Criteria Into Spent Nuclear Fuel Site Screening And Relocation, Julie M. Sorfleet

Cal Poly Humboldt theses and projects

Spent nuclear fuel, also known as nuclear waste, is the byproduct of nuclear power generation. The need for safe and responsible long-term storage and disposal of radioactive fuel presents significant technical and social challenges. These challenges are compounded by several factors, including the emerging nuclear renaissance in the United States, climate and coastal hazards, and the lack of consolidated interim or permanent storage. This research explores perceptions of risk, relocation, and siting spent nuclear fuel, predominantly focusing on Humboldt County, California. I used online surveys, the Analytic Hierarchy Process, and geographic information systems (GIS) analysis to inform how social and …

Exploring Coastal Spaces Of Tribal Sovereignty And Self-Determination In Ancestral Waters Proposed For Offshore Wind Development, Alyssa Suarez

Cal Poly Humboldt theses and projects

Proposed offshore wind development off California’s North Coast raises novel questions about Tribal sovereignty offshore. This project specifically engages claims, assuming the Yurok Tribe’s framing that offshore wind development poses a coastal hazard. The research followed a co-production framework. The research questions were co-designed with the Yurok Tribe and the research itself governed by a Data Sharing Agreement. The work presents findings from 13 semi-structured interviews with individuals and experts navigating sovereignty in the offshore wind space, including government representatives; lawyers; legal researchers; academics; foundation staff; journalists; and Humboldt Bay community members. Participants identified several key tensions surrounding claims of …

Fueling Adaptation: Collaborative Wildfire Governance In The Colorado Front Range Landscape, Mahmood Muttaqee, Cody Evers, Lindsay K. Campbell, Max Nielsen-Pincus, Olivia Awbrey, Kathryn Hixson, Michelle Johnson, Erika Svendsen

Environmental Science and Management Faculty Publications and Presentations

Collaborative governance plays a critical role in wildfire risk mitigation efforts. This study examines collaborative wildfire governance networks within the Colorado Front Range, a landscape that was designated under the USDA Forest Service's Wildfire Crisis Strategy (WCS). Collaborative governance networks in the Colorado Front Range leverage partnerships across multiple organizational actors including federal, state, and local agencies, non-profits, fire districts, and research institutions. Through survey data collected from 281 respondents revealing a collaborative network of 401 organizations, the study aimed to identify the structure, capacity, and gaps in governance networks addressing wildfire risk in the Colorado Front Range. Survey results …

Urban Heterogeneity Drives Dissolved Organic Matter Sources, Transport, And Transformation From Local To Macro Scales, Rebecca L. Hale, Kristina G. Hopkins, Krista A. Capps, John S. Kominoski, Jennifer L. Morse, Allison H. Roy, Shuo Chen, Annika Quick, Andrew J. Blinn, Liz Ortiz Muñoz, Gwendolynn Folk

Environmental Science and Management Faculty Publications and Presentations

Urbanization reshapes dissolved organic matter (DOM) sources, transport, and transformations through changes in vegetation, hydrology, and management of waste and water. Yet the impacts of urbanization on DOM are variable within and among cities. Predicting heterogeneous responses to urbanization is challenged by diverse human activities and underlying biophysical variation along stream networks. Using data from the 486 largest urban areas in the continental United States and seven focal cities, we identified macro and local scale urban gradients in social, built, and biophysical factors that are expected to shape DOM. We used these gradients and the literature to develop hypotheses about …

Theoretical Foundations And Applied Performance Of Periodicity-Aware Imputation: Variable Bandpass Block Bootstrap Methods For Incomplete Time Series, Asmaa Ahmad

Electronic Theses & Dissertations (2024 - present)

Time series data are prevalent across a wide range of disciplines, including health surveillance, public policy, and environmental monitoring. In the presence of underlying cyclical patterns, the integrity of time series analysis depends critically on the ability to detect, model, and impute structured missing data without compromising the temporal structure. This dissertation introduces and validates a novel imputation framework that integrates the Variable Bandpass Periodic Block Bootstrap (VBPBB) into multiple imputation procedures, improving the accuracy, robustness, and interpretability of time series models under high rates of missingness and noise. The overarching goal of this dissertation was to develop and evaluate …

Essays On Technological Change And Scientific Research, Max Mayca

Electronic Theses & Dissertations (2024 - present)

The primary objective of economic science has long been to understand and promote growth, as it contributes to a more prosperous civilization and improves individual well-being. The core drivers of growth—capital accumulation, human capital development, and technological progress—are well-established. While capital deepening enables scaling of production, and human capital enhances labor productivity, technological and scientific advancements remain the most critical, as they continually redefine the efficiency frontier. Given this centrality, it is essential to understand how technological progress affects labor markets, how research resources should be allocated, and how technology relates to human capital formation.

The first part of this …

Crises, Coloniality, And Energy Transformations In Puerto Rico, Laura Kuhl, Marla Perez-Lugo, Carlos Arriaga Serrano, Cecilio Ortiz Garcia, Ryan Ellis, Jennie C. Stephens

Sociology Faculty Publications

Increased attention to inclusive processes is essential to ensure injustices are not perpetuated during energy transitions. Crises, such as the collapse of the electric grid in Puerto Rico after Hurricane Maria, present the promise of opening windows of opportunity for new ideas and voices to inform the future, but they also create opportunities for powerful interests to reinforce existing power dynamics. While coloniality has been recognized as a barrier to sustainable energy transformations, greater integration of the literature on climate coloniality and sustainability transitions is needed. This chapter analyzes visions of the future of the energy system among diverse constituents …

Late Ordovician Evolution Of Sea Scorpions: Eurypterids Of The Big Hill Lagerstätte, Joseph Donaldson Bingham Jr.

Graduate Theses, Dissertations, and Problem Reports (ETD)

Eurypterids are a group of diverse chelicerates that first appeared during the Middle Ordovician (467.3 Ma) and went extinct at the end of the Permian (251.9 Ma). The fossil record of eurypterids during the Ordovician is relatively sparce, comprising only 12 species representing the Megalograptidae, a ‘waeringopterid’ clade, Rhenopteridae, Onychopterellidae, Adelophthalmoidea, and Eurypteroidea clades. This study describes early eurypterids from the Katian aged (~452 Ma) Big Hill Lagerstätte of Michigan. The described material represents two new species, herein named Machipterus margaritae sp. nov. (based on 21 specimens preserving the ventral prosoma and prosomal appendages, and opisthosoma) and Dikranopterus lysinae sp. …

Land Target Detection Algorithm In Remote Sensing Images Based On Deep Learning, Wenyi Hu, Xiaomeng Jiang, Jiawei Tian, Shitong Ye, Shan Liu

Electrical & Computer Engineering Faculty Publications

Remote sensing technology plays a crucial role across various sectors, such as meteorological monitoring, city planning, and natural resource exploration. A critical aspect of remote sensing image analysis is land target detection, which involves identifying and classifying land-based objects within satellite or aerial imagery. However, despite advancements in both traditional detection methods and deep-learning-based approaches, detecting land targets remains challenging, especially when dealing with small and rotated objects that are difficult to distinguish. To address these challenges, this study introduces an enhanced model, YOLOv5s-CACSD, which builds upon the YOLOv5s framework. Our model integrates the channel attention (CA) mechanism, CARAFE, and …

Identifying The Impacts Of Land Use/Land Cover Changes On Ecosystem Services From A Geospatial Perspective In Albany County, Kyaw Khaung Thant Zin

Electronic Theses & Dissertations (2024 - present)

Ecosystem services encompass the broad array of direct and indirect advantages that people derive from nature and its ecosystems. Considering accelerating environmental change and degradation, recognizing the importance of these services is more crucial than ever, as they illustrate the many ways in which healthy ecosystems sustain human life. However, these services are diminishing at a rapid and unprecedented rate, raising global concern over both the transformations taking place and their root causes. Among the leading threats, land-use change stands out as a particularly significant one, influenced by a variety of driving factors. Albany County, New York, characterized by its …

Evaluating Tropospheric Delay Modeling For Enhanced Geospatial Accuracy, Adeyinka Olaoluwa Olaseinde

Masters Theses

Interferometric Synthetic Aperture Radar (InSAR) is a vital technique for monitoring ground surface deformation across large spatial scales. However, variability in atmospheric water vapor, pressure, and temperature introduces tropospheric delays that can significantly affect measurement accuracy. These delays are often corrected using outputs from numerical weather prediction (NWP) models. RAiDER, an open-source Python package, facilitates this by estimating tropospheric delays using models such as the High-Resolution Rapid Refresh (HRRR). Previous studies have shown that weather model–based corrections can substantially reduce atmospheric noise in InSAR data but also highlight persistent residual errors, especially at spatial scales smaller than the model grid …

The Geography Of Rock Glaciers In The American West, Allison Reese Trcka, Andrew G. Fountain, Bryce Allen Glenn

Geology Faculty Publications and Presentations

Rock glaciers are relatively common in conterminous United States west of the 100° meridian, yet their distribution and number are not well known. Using aerial and satellite imagery, we inventoried the population of rock glaciers, yielding 2,257 rock glaciers totaling 234.28 km² with an area of uncertainty of 7 percent. Of these, 1,561 (155.44 km²) are considered intact (moving) and 696 (76.84 km²) relict. Based on published estimates of ice content, total water-equivalent volume is roughly 2.52 km³. Rock glacier elevations increase from the northwest (Washington) to the southeast (Colorado), following a spatial …

20 Years Of Light Pentaquark Searches, Moskov Amaryan

Physics Faculty Publications

In this paper, I pay tribute to my exceptional colleagues and friends Dmitri Diakonov, Victor Petrov, and Maxim Polyakov by examining the experimental progress and current status of the searches of the ϴ⁺ pentaquark from its inception to the present.

Atmospheric Chemistry Experiment (Ace) V.5.3 Winds: Validation And Model Comparisons, Matthew Wyatt, Peter F. Bernath, Chris Boone, Leo Lavy, Ryan Johnson

Physics Faculty Publications

The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) uses limb geometry to measure transmittance spectra of Earth's atmosphere by solar occultation. Line-of-sight wind speeds can be derived via Doppler shifts of molecular lines in infrared spectra. The wind look direction angles relative to geodetic north are derived from geometry. We validate the new ACE version 5.3 (v.5.3) line-of-sight winds with MIGHTI and meteor radar vector wind observations and find a -15 m s^-¹ (+15 m s^-¹) sunrise (sunset) shift above 80 km. We also compare line-of-sight winds from ACE-FTS v.5.2 and v.5.3 with vector winds from …

Spatial Analysis Of American Chestnut (Castanea Dentata) Distribution And Ecology In Kentucky’S Federal Lands, Jacob Raymond Pease

Murray State Theses and Dissertations

Anthropogenic factors have been the cause of the decline of tree species across the globe. From unsustainable logging and development to disease and improper management, threats to forests have taken their toll. The American chestnut (Castanea dentata) was once an integral basal tree species in Appalachian forests, but chestnut blight drove the species to functional extinction by the mid-1900s. The recent creation of genetically modified chestnuts gives hope for future restoration of the species throughout its historical range. Despite blight resistance, effective restoration will require optimal site selection for finding and planting chestnuts, which will maximize limited resources. …

A Paleobiological And Paleoecological Analysis Of Mississippian Trilobites With Segmentation Abnormalities, April Catherine Cerami

Graduate Theses, Dissertations, and Problem Reports (ETD)

Trilobites are a well-preserved group of arthropods, with a fossil record extending from the Cambrian to the end of the Permian. Abnormalities, such as injuries or teratological defects, have been observed and described in multiple individuals, although investigating how these abnormalities occur in populations has been largely overlooked.

One possible cause of abnormalities in marine arthropods is heavy metal pollution. Such metals can leave individuals more susceptible to teratological deformities and injuries, interfering with the molting and healing process. Here, methods for analyzing elemental composition and preservation of the trilobite cuticle were refined, finding that 30 μm thin sections are …

Ecological Resources Of A Heavily Modified And Utilised Temperate Coastal Embayment: Cockburn Sound, Peter J. Mitchell, Daniel E. Yeoh, Kurt N. Krispyn, Claire N. Greenwell, Sorcha Cronin-O’Reilly, Delphine B.H. Chabanne, Glenn A. Hyndes, Danielle Johnston, David V. Fairclough, Claire Wellington, Alan Cottingham, Gary Jackson, Jeffrey V. Norriss, Matias Braccini, Hector Lozano-Montes, Chandra P. Salgado Kent, Erin Clitheroe, Alissa Tate, James W. Penn, Marion Massam, Neil R. Loneragan, James R. Tweedley

Research outputs 2022 to 2026

Coastal environments and their associated biota provide numerous environmental, economic and societal services. Cockburn Sound, a temperate embayment on the lower west coast of Western Australia, is immensely important for the State and adjacent capital city of Perth. However, urbanisation and associated terrestrial and marine development has the potential to threaten this important ecosystem. This study collated published and unpublished data to review the current state of the ecological resources of Cockburn Sound and describe how they have changed over the past century. Post-WWII, the embayment began undergoing pronounced anthropogenic changes that limited oceanic water exchange, increased nutrient load, modified …

Ensemble Learning Models For Large-Scale Time Series Forecasting In Supply Chain, Minjuan Zhang

Dissertations

Machine learning and AI techniques are transforming supply chain forecasting, driven by the expanding availability of data assets. These advanced methods offer powerful opportunities to optimize management processes, reduce operational costs, and enhance strategic decision-making, which is crucial for enterprise success. However, conventional statistical approaches, such as Autoregressive Integrated Moving Average Models (ARIMA), dynamic regression, and Unobserved Component Models (UCMs)—which have long dominated time series forecasting—often fall short in accuracy and scalability. These traditional models face limitations in batch processing, handling large-scale data, addressing uncertainty-induced disruptions, and synchronizing demand-supply scenarios.

To address these challenges, a novel class of AI-powered ensemble …

Multi-Sensor Data Fusion And Gis-Drastic Integration For Groundwater Vulnerability Assessment With Rainfall Consideration, Wu Jiazhe, Dai Xinrui, Su Yangcheng, Zheng Xiangtian, Bushra Ghaffar, Rabiya Nasir, Ahsan Jamil, Zeeshan Zafar, Mohammad Suhail Meer, M. Abdullah-Al-Wadud, Rahila Naseer, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

In many areas of the world, particularly in arid and semi-arid regions, groundwater is the primary source of fresh water, and it supplies around one-third of the world's fresh water. Agriculture is the primary economic sector on the coast in the southern district (Nowshera). More food productivity is required due to the expanding population and diminishing agricultural lands, which increases the use of chemical pesticides and fertilizers in farming. The current study was conducted in northwestern parts of Pakistan to evaluate the impacts of the frequent use of pesticides and fertilizers in agricultural fields. Nine hydrogeological parameters were considered, and …

Composite Volume Learning Media Based On Augmented Reality To Enhance Students’ Visual-Spatial Intelligence, Ria Kurniawati, Susiswo Susiswo, Syamsul Hadi

Jurnal Pendidikan Sains

Augmented Reality (AR) technology, a three-dimensional visual tool that integrates virtual objects or environments into real-world displays in real time (Azuma et al., 2001), is particularly useful for grasping complex concepts such as the composite volume of solids, which often confuses students when they need to decompose solids into their individual components. While previous research has predominantly focused on the introduction of solids, spatial nets, and the volume of singular shapes, this study aims to develop composite volume learning media based on AR to enhance students’ visual-spatial intelligence in a valid, practical, and effective manner, aligning with their concrete operational …