Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

Engineering

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 91 - 120 of 3540

Full-Text Articles in Entire DC Network

Iterative Data Augmentation For Enhancing Deep Learning Performance With Limited Training Data, Avinash Singh Jan 2026

Iterative Data Augmentation For Enhancing Deep Learning Performance With Limited Training Data, Avinash Singh

ETDs from 2020-2029

Deep learning models have demonstrated impressive performance across different domains; however, their effectiveness heavily depends on large, well annotated datasets. In practice, data are often limited in size, leading to overfitting, poor generalization, and degraded model robustness and performance. Moreover, conventional augmentation techniques are typically static in nature, lack adaptability during training, and can produce geometrically inconsistent or unrealistic mixed images. This dissertation addresses three major challenges in data augmentation and model generalization: (1) the scarcity of labeled data and limited dataset size, (2) the absence of adaptive mechanisms for dynamically adjusting learning parameters during training, and (3) the creation …

Go to article

When Disasters Trigger Cyber Vulnerabilities: Mapping Physical-Digital Interdependencies In Critical Infrastructure Systems, Dikshya Panta, Sicheng Wang, Aditya Sapkota, Prakash Ranganathan Jan 2026

When Disasters Trigger Cyber Vulnerabilities: Mapping Physical-Digital Interdependencies In Critical Infrastructure Systems, Dikshya Panta, Sicheng Wang, Aditya Sapkota, Prakash Ranganathan

Faculty Publications

Critical infrastructure (CI) systems such as power, water, communications, and emergency services are increasingly exposed to compound risks in which natural disasters and cyber incidents interact and amplify one another. Traditional risk assessments often isolate physical and digital threats, overlooking the cascading dependencies that emerge when operational stress, emergency reconfiguration, and adversarial exploitation coincide. This study conducts a 2019–2025 scoping review and introduces a Geographic Information System (GIS) driven six-stage disaster cyber compounding framework that characterizes, maps, and operationalizes compound risk across interdependent CI sectors. The framework integrates a common operating picture, analytic situational understanding, exposure mapping, threat-fingerprint encoding, detection …

Go to article

Why Agtech Startups Fail? Evidence From Global Shutdown Patterns In 2025 And The Cost-Adoption Mismatch Effect, Ankit Chandra, Ishani Lal Jan 2026

Why Agtech Startups Fail? Evidence From Global Shutdown Patterns In 2025 And The Cost-Adoption Mismatch Effect, Ankit Chandra, Ishani Lal

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Agricultural technologies are widely seen as a driver for sustainability, resilience, and food-system transformation. Yet in 2025, agtech startup across North America, Europe, Asia, and Africa experienced multiple shutdowns. Although each company closed for its own reasons, the failures highlight consistent underlying patterns. We analyze 18 publicly reported shutdowns across controlled-environment agriculture (CEA), robotics, insect protein, digital platforms, sensors, and ag-biotechnology. We find that most ventures struggled not with scientific feasibility but with economic and adoption dynamics at the farm level. We identify a Cost-Adoption Mismatch Effect, in which the capital and operational burden of a technology exceeds farmers’ capacity …

Go to article

Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi Jan 2026

Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi

Harrisburg University Other Works

This paper conducts a comparative analysis of U.S. and Chinese frameworks for AI literacy and adoption, with focus on agentic AI and Artificial General Intelligence (AGI) systems capable of autonomous reasoning and execution. We examine national policies, educational integration, governance structures, and technological roadmaps, employing both qualitative review and quantitative modeling. Mathematical formulations include multi-dimensional literacy scoring, Bass diffusion models for adoption dynamics, risk assessment functions, regulatory effectiveness indices, competitiveness metrics, and optimization frameworks for resource allocation. Our analysis reveals divergent paradigms: the U.S. Favors decentralized, innovation-driven approaches with emphasis on interoperability and public-private collaboration; while China pursues centralized, state-led …

Go to article

Optimal Placement Of Electric Vehicle Chargers: A Mixed-Integer Linear Programming Model, Joubin Zahiri Khameneh, Emmanuel Fagbenle Jan 2026

Optimal Placement Of Electric Vehicle Chargers: A Mixed-Integer Linear Programming Model, Joubin Zahiri Khameneh, Emmanuel Fagbenle

Faculty Publications

Electric vehicle adoption is growing, but New Hampshire lags in public charging infrastructure, especially in rural areas. This gap increases range anxiety and economic inefficiencies. In this study, we developed a mixed-integer linear programming (MILP) model to optimally locate new electric vehicle chargers statewide, maximizing coverage and equity under budget constraints. The model includes geographic coverage requirements, population-weighted equity, capacity limits, and a $28 million budget. Moreover, the model recommends 855 Level 2 chargers and 149 Direct Current Fast Chargers (DCFCs) across 247 ZIP Codes, nearly doubling public charging capacity and achieving 98.8% coverage within defined service radii. The plan …

Go to article

Ai-Driven Network Orchestration: Adaptive Routing For Federated Learning Over Software-Defined Hybrid Wans, Osama Abu Hamdan Jan 2026

Ai-Driven Network Orchestration: Adaptive Routing For Federated Learning Over Software-Defined Hybrid Wans, Osama Abu Hamdan

Computer Science and Engineering Dissertations - Archive

Modern wide-area networks increasingly adopt hybrid architectures that combine high-capacity wired backbones with flexible wireless links to extend connectivity to remote and underserved locations. However, the bandwidth variability inherent in wireless segments creates routing challenges that traditional protocols, designed for static link capacities, cannot adequately address. Simultaneously, Federated Learning (FL) has emerged as a privacy-preserving distributed machine learning paradigm in which geographically dispersed clients collaboratively train shared models without exchanging raw data. When deployed over wide-area networks, FL training is severely bottlenecked by communication overhead, particularly in cross-silo settings where model payloads reach hundreds of megabytes and synchronous aggregation protocols …

Go to article

Assessment Of The Influence Of Human Activities On The Occurrence Of Forest Fires In Thailand Via Multiple Linear Regression (Mlr), Sittipong Ruktamatakul, Jirarat Insuk, Benjaporn Pinwongpet, Sarisa Ruktametakul, Pornpis Yimprayoon Jan 2026

Assessment Of The Influence Of Human Activities On The Occurrence Of Forest Fires In Thailand Via Multiple Linear Regression (Mlr), Sittipong Ruktamatakul, Jirarat Insuk, Benjaporn Pinwongpet, Sarisa Ruktametakul, Pornpis Yimprayoon

Applied Environmental Research

Forest fires represent one of the most critical environmental challenges in Thailand, with impacts varying depending on forest type, fuel characteristics, terrain conditions, fire intensity, and the frequency of fire occurrence on the same landscape. While forest fires can contribute to ecosystem degradation, biodiversity loss, and the depletion of natural resources, such effects are not uniformly severe across all forest ecosystems. Understanding the human-induced factors contributing to forest fire occurrence is crucial for developing effective prevention strategies and promoting sustainable forest management. This study aimed to identify the anthropogenic factors influencing forest fire areas in Thailand via multiple linear regression …

Go to article

Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei Jan 2026

Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei

Mechanical & Aerospace Engineering Faculty Publications

In this study, we present a replay-based framework for uncertainty-aware persistent tracking of multiple advected surface patches using an autonomous marine vehicle operating in spatiotemporal-varying currents. The method combines three components: local flow estimation, covariance-aware patch-boundary propagation with intermittent boundary fusion, and mission-level scheduling over multiple patches. Each patch is represented by a polygonal boundary, whose vertices are propagated through the estimated flow field while carrying per-vertex covariance, thereby quantifying uncertainty growth during advection. A flow-aware gain-scheduled linear quadratic regulator (LQR) was designed to shape the desired surge speed to take advantage of favorable currents. When the vehicle services a …

Go to article

Five Tensions Of Artificial Intelligence Adoption For Organ Allocation: Applying The Technology–Organization–Environment Framework, Amaneh Babaee, Daniel Burton Shank, Casey I. Canfield, Joely Grace Hall, Krista L. Lentine, Henry Randall, Mark Schnitzler Jan 2026

Five Tensions Of Artificial Intelligence Adoption For Organ Allocation: Applying The Technology–Organization–Environment Framework, Amaneh Babaee, Daniel Burton Shank, Casey I. Canfield, Joely Grace Hall, Krista L. Lentine, Henry Randall, Mark Schnitzler

Psychological Science Faculty Research & Creative Works

Background: The US organ transplantation system is pursuing modernization of the allocation process through the integration of new technologies such as artificial intelligence (AI). However, the legal and ethical issues within the transplantation industry are still of concern. Objective: We explore the opportunities and challenges for Organ Procurement Organizations (OPOs) to adopt AI. The US organ transplant system is a highly regulated industry yet open to innovation. Methods: Ten structured interviews were conducted with OPO representatives using the Extended Technology, Organization, Environment (TOE) framework. Results: Overall, we identified five core tensions in AI adoption: (1) misconceptions, (2) approach to training, …

Go to article

Skin Type Diversity In Image Datasets, Neda Alipour Jan 2026

Skin Type Diversity In Image Datasets, Neda Alipour

Doctoral

Image-based AI systems that analyse human skin are increasingly used in healthcare and computer vision applications. However, many human skin-based image datasets do not provide reliable information about skin type, making it difficult to assess whether these systems perform consistently across the full spectrum of skin colour. The objective of this thesis is to examine how skin type diversity is represented and measured in image datasets, and to evaluate the reliability of image-based skin type measurement methods under different imaging conditions. Using publicly available skin lesion image datasets as a well-defined and widely used sub-class of skin image datasets, this …

Go to article

Beyond Receptive Measures: Development And Validation Of The Spatial Grid Drawing Assessment (Sgda) As A Productive Measure Of Spatial Skill, Katrina L. Carlson Jan 2026

Beyond Receptive Measures: Development And Validation Of The Spatial Grid Drawing Assessment (Sgda) As A Productive Measure Of Spatial Skill, Katrina L. Carlson

Dissertations, Master's Theses and Master's Reports

Spatial skills are vital in many STEM disciplines, starting at or prior to university training, and often extending throughout one’s career. The most widely used spatial ability measures (e.g., PSVT: R, MRT) rely on what I refer to as receptive skills: examining an object or design, mentally transforming it, and comparing it to given alternatives. But because work in many STEM disciplines also involves productive spatial skill such as drawing, I hypothesize that a productive measure of spatial skill may predict distinct aspects of spatial ability. This research investigates the relationship between traditional receptive Spatial Visualization (SV) assessments, such as …

Go to article

Assessment Of Truck Parking Demand And Safety During Normal And Severe Weather Conditions In Nebraska, Nathan Huynh, Li Zhao, Zhenghong Tang, Aida Riahifar, Jahangeer Jahangeer Jan 2026

Assessment Of Truck Parking Demand And Safety During Normal And Severe Weather Conditions In Nebraska, Nathan Huynh, Li Zhao, Zhenghong Tang, Aida Riahifar, Jahangeer Jahangeer

Nebraska Department of Transportation: Research Reports

This project examined truck parking capacity, demand, and utilization patterns along I-80 in Nebraska. The objectives were to (1) document the capacity of public and private truck parking facilities along I-80, (2) analyze spatial and temporal trends in parking demand, (3) develop models to predict occupancy at parking facilities, (4) identify clusters of undesignated parking during inclement weather, and (5) assess whether truck parking shortages contribute to truck-involved crashes. Within a one-mile buffer of I-80, 21 public facilities and 49 private facilities were identified. The spatiotemporal analysis of these public and private truck parking facilities using the National Agriculture Imagery …

Go to article

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio Jan 2026

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio

VMASC Publications

Prior research on power-law distributions has primarily focused on modeling frequency patterns, with less attention given to rank distributions and how ranked positions reflect relative importance among elements. In discrete power-law distributions, frequency-based metrics often provide limited discrimination in the tail, where elements may exhibit similar counts but differ in relative dominance. These patterns are especially evident, for instance, in academic publishing, where keywords, affiliations, and citations commonly exhibit power-law behavior. To address this limitation, we introduce the Relative Importance Factor (RIF) Index, a statistical measure derived from the estimated discrete power-law rank distribution rather than an additional independent parameter. …

Go to article

Analysis Of Policies And Incentives For The Successful Implementation Of Hydrogen-Fueled Medium-Duty And Heavy-Duty Vehicles In Humboldt County, California, Alka Verma Jan 2026

Analysis Of Policies And Incentives For The Successful Implementation Of Hydrogen-Fueled Medium-Duty And Heavy-Duty Vehicles In Humboldt County, California, Alka Verma

Cal Poly Humboldt theses and projects

The 21st century has seen a significant rise in global greenhouse gas (GHG) emissions, with the transportation sector contributing 23% of these emissions. Medium-duty and heavy-duty vehicles (MD/HD) are particularly impactful, accounting for over a quarter of transport-related emissions. In Humboldt County, California, transportation represents 53% of total emissions, with MD/HD vehicles being a major contributor. As light-duty vehicles shift to zero-emission alternatives, the MD/HD sector faces unique challenges. Hydrogen fuel cell vehicles offer a promising solution, providing longer range, higher energy density, and quicker refueling compared to battery electric vehicles (BEVs). These features make hydrogen an attractive option for …

Go to article

Powering The Machine, Draining The Planet: Whether U.S. Environmental Law Is Equipped To Regulate The Energy And Water Demands Of Ai Data Centers, Michael Marcu Jan 2026

Powering The Machine, Draining The Planet: Whether U.S. Environmental Law Is Equipped To Regulate The Energy And Water Demands Of Ai Data Centers, Michael Marcu

Journal of Earth and Life Science

Artificial intelligence (AI) data centers have become one of the United States' fastest-growing and least-regulated sources of environmental stress. In 2024 alone, U.S. data centers consumed 183 terawatt-hours (TWh) of electricity more than the entire nation of Pakistan and consumed an estimated 17 billion gallons of water (IEA, 2025; Berkeley Lab, 2024). By 2030, electricity demand from these facilities is projected to reach 426 TWh, a 133% increase in six years (Pew Research Center, 2025). This paper examines whether the existing U.S. environmental regulatory framework put by the National Environmental Policy Act (NEPA), the Clean Water Act (CWA), and the …

Go to article

Climate And Seasonal Influences On Indo-Pacific Sea Level: Insights From 30 Years Of Satellite And Tide Gauge Data, Karlina Triana Jan 2026

Climate And Seasonal Influences On Indo-Pacific Sea Level: Insights From 30 Years Of Satellite And Tide Gauge Data, Karlina Triana

ASEAN Journal on Science and Technology for Development

We analyze Indo-Pacific sea-level variability using monthly satellite altimetry (1993–2025) validated against records from 16 tide-gauge stations. Cross-comparisons show strong agreement, especially in the western Pacific, confirming the reliability of altimetry for regional assessments. Seasonal SLA variability is largest in the Bay of Bengal and South China Sea and reflects monsoonal forcing, whereas interannual fluctuations in the eastern Indian and western Pacific oceans are dominated by ENSO and modulated by PDO. Harmonic decomposition isolates annual and semi-annual cycles, and an EOF/PCA framework identifies the leading modes: EOF1 (30.8%) captures basin-scale interannual variability and EOF2 (20.9%) reflects the seasonal cycle. Spectral …

Go to article

A Hybrid Geospatial And Remote Sensing Methodology For Drought Vulnerability Assessment In Semi-Arid Ecosystems, Kaifi Fakhir Chomani Jan 2026

A Hybrid Geospatial And Remote Sensing Methodology For Drought Vulnerability Assessment In Semi-Arid Ecosystems, Kaifi Fakhir Chomani

Mansoura Engineering Journal

The Kurdistan Region of Iraq (KRI) faced significant drought challenges due to global and environmental changes, necessitating drought assessments. Advanced techniques of remote sensing, Geographic Information Systems (GIS), and Analytic Hierarchy Process (AHP) were combined in this research to perform drought vulnerability zonation for KRI. Average annual rainfall, Average number of rainy days, Average annual temperature, slope, elevation, normalised difference water index (NDWI), normalised difference vegetation index (NDVI), land surface temperature (LST), and temperature condition index (TCI) were selected as contributing parameters for drought vulnerability assessments. The considered parameters were weighted using pairwise comparison, and thematic maps were created to …

Go to article

Workshop Outcomes Report: 2nd International Workshop On Seismic Resilience Of Arctic Infrastructure And Social Systems, Majid Ghayoomi, Daniela Morganti Jan 2026

Workshop Outcomes Report: 2nd International Workshop On Seismic Resilience Of Arctic Infrastructure And Social Systems, Majid Ghayoomi, Daniela Morganti

Faculty Publications

The report provides an overview of the second international workshop on Seismic Resilience of Arctic Infrastructure and Social Systems. The report discusses agenda, workshop activities, interdisciplinary working groups, and results. It ends with several strategic questions and investigation plans that were developed as part of the workshop activities.

Go to article

Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective, Dan Liu Jan 2026

Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective, Dan Liu

Journal of International Technology and Information Management

While crowdfunding is often heralded as a democratized funding avenue that empowers women with higher success rates, this study reveals a more nuanced picture of gender dynamics. The Stereotype Content Model suggests that women are often perceived as warmer but less competent. Using a large dataset from Kickstarter, we find that female-led projects can attract more backers, likely due to warmth-driven appeal, but receive smaller average contributions, potentially due to concerns about risk linked to lower perceived competence. However, the total funding raised by female-led campaigns is comparable to that of male-led ones, showing no clear advantage or disadvantage. This …

Go to article

The Role Of Ict In Enhancing National Logistics Performance And Economic Productivity, Jin Ho Kim Jan 2026

The Role Of Ict In Enhancing National Logistics Performance And Economic Productivity, Jin Ho Kim

Journal of International Technology and Information Management

This study sheds light on the transformative impact of Information and Communication Technology (ICT) on national productivity via logistics performance. By distinguishing between mobile and wired Internet speeds, the research demonstrates how these technologies influence logistics performance and, in turn, national productivity across different economic contexts. The findings reveal a nuanced relationship between ICT and logistics performance, with mobile ICT playing a more significant role in developing countries due to its accessibility and cost-effectiveness. In contrast, developed countries benefit from a balanced integration of both mobile and wired ICT. Moreover, the study highlights the mediating role of logistics performance in …

Go to article

Climate Change Impacts On Hydrology In The Upper James Watershed, Imiya Mudiyanselage Chathuranika, Dalya Ismael Jan 2026

Climate Change Impacts On Hydrology In The Upper James Watershed, Imiya Mudiyanselage Chathuranika, Dalya Ismael

Engineering Technology Faculty Publications

Hydrological modeling of the Upper James Watershed (UJW), Virginia, is critical for predicting water availability, flood management, agriculture, ecosystem protection, and hydropower production under increasing climate change. The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) is applied to evaluate climate change impacts on key hydrological components within the watershed. Future climate conditions were assessed for the near (NF: 2026-2050), mid (MF: 2051-2075), and far (FF: 2076-2100) periods using three Global Climate Models (GCMs) under Shared Socioeconomic Pathways SSP 2-4.5 and SSP 5-8.5. Climate data were bias-corrected using the Linear Scaling Method (LSM) and used to drive the HEC-HMS model. Results project …

Go to article

Choice-Based Crowdshipping For Next-Day Delivery Services: A Dynamic Task Display Problem, Alp Arslan, Firat Kilci, Shih-Fen Cheng, Archan Misra Jan 2026

Choice-Based Crowdshipping For Next-Day Delivery Services: A Dynamic Task Display Problem, Alp Arslan, Firat Kilci, Shih-Fen Cheng, Archan Misra

Research Collection School Of Computing and Information Systems

This paper studies integrating the crowd workforce into next-day home delivery services. In this setting, both crowd drivers and contract drivers collaborate in making deliveries. Crowd drivers have limited capacity and can choose not to deliver if the presented tasks do not align with their preferences. The central question addressed is: How can the platform minimize the total task fulfilment cost, which includes payouts to crowd drivers and additional payouts to contract drivers for delivering the unselected tasks by customizing task displays to crowd drivers? To tackle this problem, we formulate it as a finite-horizon Stochastic Decision Problem, capturing crowd …

Go to article

Land Use And Land Cover Simulation Via Integrated Modelling With Gis Techniques For Sustainable Land Utilization Development In The Northeast Khong Subwatershed Of Thailand, ฺBanchongsak Faksomboon, Thipphaphone Keoviyavong Jan 2026

Land Use And Land Cover Simulation Via Integrated Modelling With Gis Techniques For Sustainable Land Utilization Development In The Northeast Khong Subwatershed Of Thailand, ฺBanchongsak Faksomboon, Thipphaphone Keoviyavong

Applied Environmental Research

Land utilization is an important indicator of socioeconomic and environmental changes caused by both natural and man-made factors. Land use and land cover (LULC) simulation is a critical tool for monitoring and predicting LULC and is essential for sustainable development, land resource management and planning. The cellular automata (CA) Markov model is the basis for the current study’s prediction of LULC changes in the Northeast Khong Sub Watershed (NKSW). Landsat data from 2013 to 2023 were used to investigate LULC classification and determine the spatiotemporal distributions of LULC. In addition, LULC data from 2013 and 2023 were used to generate …

Go to article

Spatial Modeling Of Natural Disaster Risk By Integrating Hazard, Vulnerability, And Exposure Factors Using Geospatial Techniques : Evidence From Mueang Tak District, Thailand, Suphatphong Ruthamnong Jan 2026

Spatial Modeling Of Natural Disaster Risk By Integrating Hazard, Vulnerability, And Exposure Factors Using Geospatial Techniques : Evidence From Mueang Tak District, Thailand, Suphatphong Ruthamnong

Applied Environmental Research

This study presents a comprehensive multihazard risk assessment for Mueang Tak District, Thailand, that integrates hazard, vulnerability, and exposure (H-V-E) dimensions. By utilizing geographic information systems (GIS) and remote sensing, the analytic hierarchy process (AHP) was employed to prioritize critical risk factors. GIS analysis integrated multisource spatial data, including Landsat 9 and Sentinel-2 imagery, CHIRPS precipitation, and SRTM-derived topography, while AHP weights were established on the basis of expert judgment and socioeconomic indices such as the relative wealth index (RWI) and population statistics. The results delineate distinct spatial risk clusters: high landslide potential is concentrated in the steep terrain of …

Go to article

Seasonal Variations In Co2 Emission From Poultry Manure-Amended Soils In Two Contrasting Tropical Agroecosystems, Gladys M. Akande, Adebayo J. Adeyemo, Chidozie J. Oraegbunam, Iduh J.J. Otene, Ezekiel C. Are, Babatunde S. Ewulo, Chioma M. Ahukaemere, Samuel O. Kolawole, Sunday E. Obalum Jan 2026

Seasonal Variations In Co2 Emission From Poultry Manure-Amended Soils In Two Contrasting Tropical Agroecosystems, Gladys M. Akande, Adebayo J. Adeyemo, Chidozie J. Oraegbunam, Iduh J.J. Otene, Ezekiel C. Are, Babatunde S. Ewulo, Chioma M. Ahukaemere, Samuel O. Kolawole, Sunday E. Obalum

Applied Environmental Research

The soil remains the largest carbon sink, the capacity of which varies spatiotemporally and with anthropogenic activities, with implications for carbon dioxide (CO2) emissions and associated global warming. Despite the increasing popularity of organic amendments in the ecologically and anthropoculturally diverse farming systems of tropical Africa, manure-induced CO2 emissions in this region with high soil-carbon-sequestration potential are poorly documented. This study assessed seasonal CO2 emissions from poultry manure-amended sandy-clay-loam and sandy-loam soils in the Rainforest-Savannah and Southern Guinea Savannah zones, respectively, of Nigeria. Following manure application at 3 rates (0, 10, and 15 t ha-1), soil samples were collected during …

Go to article

Assessing Forest Fragmentation And Edge Expansion In Nan Province, Thailand, Using Landsat Data (2014–2022), Kasidit Rison, Marut Fuangarworn, Chatchawan Chaisuekul Jan 2026

Assessing Forest Fragmentation And Edge Expansion In Nan Province, Thailand, Using Landsat Data (2014–2022), Kasidit Rison, Marut Fuangarworn, Chatchawan Chaisuekul

Applied Environmental Research

The increasing pressure from land-use change and agricultural expansion in Nan Province, northern Thailand, has accelerated forest fragmentation and reduced the ecosystem service value (ESV) of the landscape. This study aims to: assess land use and forest fragmentation change in Nan Province between 2014 and 2022, and evaluate the impact of land use change on ESV. Landsat 8 OLI satellite imagery from 2014 and 2022 was used to classify land cover into five types: forest, agriculture, settlements, exposed soil, and others. Forest fragmentation was evaluated using landscape metrics such as patch number, mean patch size, edge length, and core area. …

Go to article

Evaluating Sediment Control Strategies Using Swat Based Bmp Assessment In A Tropical Highland Watershed, Northern Thailand, ฺBanchongsak Faksomboon, Wilailak Suanmali Jan 2026

Evaluating Sediment Control Strategies Using Swat Based Bmp Assessment In A Tropical Highland Watershed, Northern Thailand, ฺBanchongsak Faksomboon, Wilailak Suanmali

Applied Environmental Research

Soil erosion remains a critical environmental challenge in the tropical highland watersheds of Southeast Asia, where steep terrain, intense monsoonal rainfall, and intensive land use interact to accelerate sediment generation and downstream degradation. This study aims to quantify spatial patterns of sediment yield and to systematically evaluate the effectiveness of individual and combined best management practices (BMPs) at both the watershed and subwatershed (SWW) scales using the Soil and Water Assessment Tool (SWAT) in a tropical highland watershed in northern Thailand. Baseline simulations reveal pronounced spatial heterogeneity in erosion severity, with substantial portions of the watershed exhibiting moderate to extreme …

Go to article

Weekly Spatiotemporal Dynamics Of Forest Fire Hotspots In Tak Province, Thailand : A Gis-Based Directional Analysis, Suphatphong Ruthamnong Jan 2026

Weekly Spatiotemporal Dynamics Of Forest Fire Hotspots In Tak Province, Thailand : A Gis-Based Directional Analysis, Suphatphong Ruthamnong

Applied Environmental Research

Forest fires are recurrent dry-season hazards in northern and western Thailand, yet their short-term spatial dynamics remain insufficiently understood. In this study, weekly spatiotemporal dynamics of forest fire hotspots in Tak Province, Thailand, were examined using Visible Infrared Imaging Radiometer Suite (VIIRS) active-fire data and GIS-based directional analysis. Hotspots from five fire seasons (2021–2025) were grouped into 24 weekly intervals beginning on 1 December. The analysis integrated weekly hotspot counts, forest-type compositions, mean-center trajectories, standard deviational ellipses, temporal changes in topographic characteristics, and fishnet-based hotspot persistence mapping. The results revealed that fire activity was highly concentrated during the middle of …

Go to article

Federated And Explainable Spiking Neural Networks For Fair And Privacy-Preserving Nail Disease Diagnostics, Ch Pavani Reddy, Krishnanaik Vankdoth Jan 2026

Federated And Explainable Spiking Neural Networks For Fair And Privacy-Preserving Nail Disease Diagnostics, Ch Pavani Reddy, Krishnanaik Vankdoth

Mansoura Engineering Journal

Automated nail disease diagnostics provide a non-invasive pathway for identifying underlying systemic health conditions; however, conventional centralized deep learning approaches often raise concerns related to privacy, fairness, and interpretability. Although the original NeuroNail-SNN framework demonstrated an energy-efficient and edge-ready diagnostic solution, its broader clinical adoption remained limited by unresolved trust, transparency, and ethical considerations. In this study, we propose the Federated and Explainable NeuroNail-SNN, which extends the original spiking neural architecture by integrating federated learning (FL), explainable artificial intelligence (XAI), fairness evaluation, and uncertainty quantification within a unified framework. Federated learning enables decentralized model training across hospitals and mobile clinics …

Go to article

Exploring Drone Technology For The Survey And Documentation Of Aerospace Archaeology Sites, David G. Morgan, Thomas R. Allen Jan 2026

Exploring Drone Technology For The Survey And Documentation Of Aerospace Archaeology Sites, David G. Morgan, Thomas R. Allen

Political Science & Geography Faculty Publications

This research examines the implementation of Unmanned Aerial Systems (UAS) during a pilot mission in Nike Park to support its aerospace preservation. Located in Carrollton, Virginia, it was a Cold War missile installation that formed part of the area’s air-defense network. This project aims to use a drone to capture high-resolution video and imagery of Nike Park’s Administrative Office Supply and PX building and the Nike Ajax missile to create virtual 3D models for the Isle of Wight County Museum’s exhibit. For this mission, the DJI Mini 4 Pro drone manually flew a circular flight pattern around the missile and …

Go to article

First Prev Next Last