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Full-Text Articles in Entire DC Network
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 23, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 23, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 26, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 26, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 28, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 28, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 30, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 30, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 35, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 35, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 36, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 36, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 37, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 37, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 77, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 77, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 77 Lidar, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 77 Lidar, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 22, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 22, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 24, Yiming Yang, Jeremy P. Bos
Wads 3d Object Detection Dataset (Wads-3d) - Sequence 24, Yiming Yang, Jeremy P. Bos
WADS-3D
WADS-3D is a standard KITTI-format dataset designed for analyzing 3D object detection robustness in severe winter weather. Addressing the need for granular analysis of perception failure in snow, the dataset includes 4,100 frames and over 30,000 labeled car instances captured during heavy snowfall and winter-storm conditions. Derived from the large-scale multimodal WADS dataset, WADS-3D enables researchers to move beyond qualitative weather assessments and systematically evaluate how varying heavy snowfall intensities impact a wide range of neural network detectors.
Green Technology: A Systematic Review Of Ai And Iot Solutions For A Sustainable Future, Nesma Abd El-Mawla, Mohamed A. Berbar, Nawal A. El-Fishawy, Mohamed A. El-Rashidy, Mahmoud Badawy
Green Technology: A Systematic Review Of Ai And Iot Solutions For A Sustainable Future, Nesma Abd El-Mawla, Mohamed A. Berbar, Nawal A. El-Fishawy, Mohamed A. El-Rashidy, Mahmoud Badawy
Mansoura Engineering Journal
Green technology offers a solution to the pressing environmental crisis. It can change the structure and generation of waste so as not to harm the earth, and people can become environmentally friendly. To address complex environmental challenges like climate change and pollution, innovative Artificial Intelligence (A.I.) and Internet of Things (IoT) solutions are essential. These technologies can help optimize resource use, reduce waste, and promote sustainable development. However, it's crucial to balance economic growth, social equity, and environmental protection when implementing green technologies. This survey paper systematically examines the landscape of Green Technology, focusing on its pivotal components: Measures of …
Print, Pattern, Stick: Low–Cost Gecko–Inspired Adhesives Using Embedded Diffraction Structures, Motaz Hassan, Oluwafemi Fayomi, Ajay Mahajan, Joshua Faust
Print, Pattern, Stick: Low–Cost Gecko–Inspired Adhesives Using Embedded Diffraction Structures, Motaz Hassan, Oluwafemi Fayomi, Ajay Mahajan, Joshua Faust
University Research
Gecko-inspired adhesives offer strong, reversible, and directionally tunable adhesion, yet fabrication methods often depend on cleanroom lithography or proprietary molds, limiting scalability and accessibility. This study presents a low-cost, modular fabrication strategy combining high-resolution digital light processing 3D printing with 1000 lines/mm optical diffraction gratings to create hierarchical elastomeric adhesives. The resulting structures feature macroscale micropillars and embedded sub-micron surface topography, enabling effective contact splitting without advanced microfabrication. Mechanical testing reveals a nonlinear increase in shear performance with contact area, with maximum shear forces exceeding 80 N at 103.2 cm2. Peel testing across varied angles and surface areas demonstrates anisotropic …
Challenges And Opportunities In Lentivirus Viral Vector Manufacturing For In Vivo Applications, Eduardo Barbieri, Caryn Heldt
Challenges And Opportunities In Lentivirus Viral Vector Manufacturing For In Vivo Applications, Eduardo Barbieri, Caryn Heldt
Michigan Tech Publications
The clinical success of chimeric antigen receptor (CAR) T-cell therapies has revolutionized oncology, yet the high costs and logistical complexities of ex vivo manufacturing remain significant barriers to global patient access. In vivo cell therapy, which involves the direct injection of lentiviral vectors (LVVs) to engineer cells within the patient’s body, offers a promising, cost-effective alternative. However, transitioning from ex vivo to in vivo applications necessitates a fundamental shift in LVV biomanufacturing to ensure safety and efficacy. This paper examines the critical bottlenecks in the current LVV production landscape. In upstream processing, we explore LVV particle assembly and maturation mechanisms, …
Neurocore: A Gnn Approach To Configurable Ip Core Identification In Fpga Netlists, Dallin Dahl, Keenan Faulkner, James Usevitch, Jeffrey Goeders
Neurocore: A Gnn Approach To Configurable Ip Core Identification In Fpga Netlists, Dallin Dahl, Keenan Faulkner, James Usevitch, Jeffrey Goeders
Student Works
Netlist reverse engineering enables many applications, including detecting IP theft, verifying CAD tool correctness, and detecting hardware trojans. However, reconstructing high-level information and circuit structure from a flat, nameless netlist is challenging. In this work we focus on the problem of locating known IP cores in an FPGA netlist, which is especially challenging due to the prevalence of highly configurable IP cores. We present Neurocore: a graph neural network-based approach to classifying nodes in a netlist as instances of known IP cores, and present and evaluate different models for different use cases. We have created a large open-source dataset of …
Mycelium-Based Composites Using Minimally Processed Industrial Hemp Biomass: Impact Of Species And Feedstock Ratio On Mechanical Performance Compared To Polystyrene Packaging, Radika Bhaskar, Tanisha Rutledge, Kevin Trangone, Oneal Latimore
Mycelium-Based Composites Using Minimally Processed Industrial Hemp Biomass: Impact Of Species And Feedstock Ratio On Mechanical Performance Compared To Polystyrene Packaging, Radika Bhaskar, Tanisha Rutledge, Kevin Trangone, Oneal Latimore
School of Design and Engineering Papers
Mycelium-based composites (MBCs\) are formed from lignocellulosic substrates and biopolymer matrices derived from fungal mycelium. Due to their low fossil energy demand and biodegradability, MBCs represent a versatile and sustainable material suitable for a range of applications, with increasing interest focused on packaging. Hemp fibers are an example of natural fibers with great promise as a substrate to improve the mechanical properties of MBCs. However, the separation of bast and hurd fiber requires processing and commercial-scale facilities that are logistically challenging and may be cost-prohibitive. Here, the potential for minimally processed hemp, with no separation of fibers, is evaluated for …
Silent Sabotage: Internal State Triggered Backdoor Attacks On Llm-Powered Robotic Systems, Doniyorkhon Obidov, Shivayogi Akki, Tan Chen, Kaichen Yang
Silent Sabotage: Internal State Triggered Backdoor Attacks On Llm-Powered Robotic Systems, Doniyorkhon Obidov, Shivayogi Akki, Tan Chen, Kaichen Yang
Michigan Tech Publications
The integration of Large Language Models (LLMs) into robotic control systems is enabling a new generation of autonomous agents capable of complex reasoning and planning. While this paradigm shift accelerates progress, it also introduces novel security risks that remain largely unexplored. Current research into LLM backdoors has focused on attacks triggered by external stimuli, such as specific words, visual objects, or environmental states. These attacks, while potent, overlook a more insidious class of vulnerability where the trigger is internal to the agent’s own operational logic. This paper presents the first comprehensive study of history-based backdoor attacks on LLM-powered robotic systems. …
Data File For Kaizen Event Research, Jen Schoenherr
Data File For Kaizen Event Research, Jen Schoenherr
Michigan Tech Research Data
Research was performed to determine if Kaizen teams that used Cartooning as one of the lean tools available for problem solving were more successful in achieving the stated Kaizen goals
Construction Project Performance Research: A Bibliometric, Scientometric, And Qualitative Review (1989–2023), Abdelnaser Abdelhameed, Mohamed S. Yamany, Ahmed Abdelaty, Emad Elbeltagi
Construction Project Performance Research: A Bibliometric, Scientometric, And Qualitative Review (1989–2023), Abdelnaser Abdelhameed, Mohamed S. Yamany, Ahmed Abdelaty, Emad Elbeltagi
Faculty Publications
Despite the significant increase in publications on construction project performance (CPP), there is a deficiency of research that rigorously assesses and synthesizes previous studies to delineate the field’s development, themes, and research gaps. This article employs quantitative and qualitative methodologies to critically evaluate studies on CPP published over the last three decades and indexed in the Scopus database. The quantitative approach includes bibliometric searches and scientometric analyses to assess the extent of research interest and achievements. The qualitative methodology aims to conduct thorough content analysis to classify existing material based on prevalent themes. The results demonstrate an exponential growth of …
After A Wildfire: Considerations For Building Environmental Testing, Andrew J. Whelton, E. Bollens, C. Ferrarezzi
After A Wildfire: Considerations For Building Environmental Testing, Andrew J. Whelton, E. Bollens, C. Ferrarezzi
Resilience to Emergencies and Disasters
No abstract provided.
Ice-Templated Zwitterionic Sponge Hydrogels For Stable And Efficient Solar Desalination In High-Salinity Brines, Louis D. Zhang, Yanhui Zhang, Peng Xiao, Chang Zhang
Ice-Templated Zwitterionic Sponge Hydrogels For Stable And Efficient Solar Desalination In High-Salinity Brines, Louis D. Zhang, Yanhui Zhang, Peng Xiao, Chang Zhang
University Research
Solar-driven steam generation (SSG) offers a sustainable pathway for desalination, yet achieving temperature-regulated control over macroporous structures in salt-tolerant hydrogels remains a critical challenge. Here, we report a carbon black-coated PDMAPS sponge hydrogel (PDMAPS-CB-SH) fabricated via an ice-templated polymerization strategy, where the pore size and connectivity are tuned by regulating ice-crystal growth at different prefreezing temperatures. The optimized PDMAPS-CB-SH integrates abundant interconnected pores with the intrinsic antipolyelectrolyte effect of zwitterionic networks, enabling rapid water transport and stable swelling in brines up to 10 wt % NaCl. Upon incorporation of carbon black nanoparticles, the hydrogel evaporator achieves a high evaporation rate …
Fiscal Year 2023 Fhwa-536 Report For The Kentucky Transportation Cabinet, Doug Kreis, Candice Wallace, Bryan Gibson, Sarah Mccormack
Fiscal Year 2023 Fhwa-536 Report For The Kentucky Transportation Cabinet, Doug Kreis, Candice Wallace, Bryan Gibson, Sarah Mccormack
Kentucky Transportation Center Research Report
Every other year, the Federal Highway Administration (FHWA) requires that states submit a Local Highway Finance Report (FHWA-536) to the agency. This report summarizes data on local highway finances and is used by FHWA to evaluate relationships between and changes in revenues, expenditures and investment patterns, and financial trends. This report presents information submitted by Kentucky in its fiscal year (FY) 2023 FHWA-536. Total receipts from local, state, and federal sources used for road and street infrastructure equaled approximately $1.11 billion. Local sources of funding accounted for the largest share of total receipts (47%), followed by state government sources (45%), …
Kytc Digital Project Delivery Phase 1 Summary, Rachel Catchings
Kytc Digital Project Delivery Phase 1 Summary, Rachel Catchings
Kentucky Transportation Center Research Report
The Kentucky Transportation Cabinet (KYTC) launched its Digital Project Delivery (DPD) Initiative in September 2020 with the goal of expanding the use of digitally formatted plan and project information throughout the transportation asset life cycle, from project delivery through asset management. KYTC retained Kentucky Transportation Center (KTC) staff with expertise in construction and design to facilitate DPD implementation. This document summarizes DPD-related efforts undertaken by the Cabinet over the past five years. Key activities completed during this period include a survey of Kentucky Association of Highway Contractors members to document their perspectives on design file usage and preferences, coordinating multiple …
Afit By The Numbers, Fy25, Air Force Institute Of Technology
Afit By The Numbers, Fy25, Air Force Institute Of Technology
AFIT Documents
AFIT’s mission is to educate defense professionals to innovatively accomplish the deterrence and warfighting missions of the USAF and USSF. AFIT’s vision of leading defense-focused education, research and consultation to accelerate military superiority across all domains is accomplished through operationally relevant advanced academic education, research, and professional continuing education.
Kentucky Cdl Adjudication Pilot And Compliance Needs Study, Jeeyen Koo, Andrew Martin, Jennifer Walton
Kentucky Cdl Adjudication Pilot And Compliance Needs Study, Jeeyen Koo, Andrew Martin, Jennifer Walton
Kentucky Transportation Center Research Report
This report examines trends in how Kentucky District Courts have adjudicated charges related to commercial driver’s license (CDL) and commercial motor vehicles (CMVs). Using court data, researchers evaluated historical patterns in charge filing volumes as well as conviction, dismissal, amendment, and diversion rates. Between 2002 and 2024, conviction rates declined and dismissals increased. Convictions peaked in the mid-70% range in the early 2000s, but fell to the mid-50% range by 2024. Speeding and other serious traffic violations — many of which are advanceable offenses — were dismissed or amended at rates that could have substantively affected the integrity of CDL …
Fiscal Year 2024 Fhwa-536 Report For The Kentucky Transportation Cabinet, Doug Kreis, Candice Wallace, Bryan Gibson, Sarah Mccormack
Fiscal Year 2024 Fhwa-536 Report For The Kentucky Transportation Cabinet, Doug Kreis, Candice Wallace, Bryan Gibson, Sarah Mccormack
Kentucky Transportation Center Research Report
Every other year, the Federal Highway Administration (FHWA) requires that states submit a Local Highway Finance Report (FHWA-536) to the agency. This report summarizes data on local highway finances and is used by FHWA to evaluate relationships between and changes in revenues, expenditures and investment patterns, and financial trends. This report presents information submitted by Kentucky in its fiscal year (FY) 2024 FHWA-536. Total receipts from local, state, and federal sources used for road and street infrastructure equaled approximately $1.27 billion. Local sources of funding accounted for the largest share of total receipts (50%), followed by state government sources (41%), …
Coe Annual Technical Review 2025, Jianshun Zhang, Bing Dong
Coe Annual Technical Review 2025, Jianshun Zhang, Bing Dong
SyracuseCoE
No abstract provided.
The Role Of Spatial Abilities In Stem Learning And The Influence Of Individual Differences, Styliani Malkogeorgou
The Role Of Spatial Abilities In Stem Learning And The Influence Of Individual Differences, Styliani Malkogeorgou
Masters
Students’ decisions to pursue education and careers in Science, Technology, Engineering, and Mathematics (STEM) are shaped by an interplay of cognitive, social, and motivational factors. Spatial ability is among the most reliable predictors of STEM success, yet less is known about how it relates to students’ STEM attitudes and aspirations, and whether visuospatial working memory (VSWM) explains this relationship. This study tested the hypotheses that (a) stronger spatial abilities and VSWM would be associated with more positive STEM attitudes and stronger STEM aspirations, and (b) VSWM would mediate the relationship between spatial abilities and STEM attitudes/aspirations, while examining the influence …
Artificial Neural Network Model For Predicting Fatigue Endurance Limit Of Hot Mix Asphalt Using Uniaxial Tension–Compression Tests, Prashanta Kumar Acharjee, Mayzan Isied, Mena I. Souliman, Sameer Jung Karkl, Tanvir Ahmed, Gokhan Saygili
Artificial Neural Network Model For Predicting Fatigue Endurance Limit Of Hot Mix Asphalt Using Uniaxial Tension–Compression Tests, Prashanta Kumar Acharjee, Mayzan Isied, Mena I. Souliman, Sameer Jung Karkl, Tanvir Ahmed, Gokhan Saygili
Civil Engineering Faculty Publications and Presentations
Fatigue is one of the major distresses occurring in asphalt concrete pavement. Repeated traffic loading causes escalated structural damage which results in the formation of cracks. There is a strain level below which the Hot Mix Asphalt goes under fatigue failure, and it is called endurance limit. In this study, a predictive model is developed to predict endurance limit strain values by using artificial neural network. Uniaxial tension-compression fatigue test results conducted under NCHRP Project 9–44 A were utilized in the model development process. An equation is also extracted from the model along which gives the exact values as the …
Characterization Of Sediment Loads And Size Distribution In Nebraska Roadway Runoff, Bruce I. Dvorak, David M. Admiraal, Pavel Shrestha
Characterization Of Sediment Loads And Size Distribution In Nebraska Roadway Runoff, Bruce I. Dvorak, David M. Admiraal, Pavel Shrestha
Nebraska Department of Transportation: Research Reports
The Nebraska Department of Transportation (NDOT) must manage sediment, and pollutant loads from roadway runoff to meet stormwater regulations. The SAFL Baffle, a hydrodynamic separator used by NDOT, depends on reliable estimates of total suspended solids (TSS) and particle size distribution (PSD). However, limited data exists for Nebraska roadways. In this study stormwater runoff was monitored at four NDOT-maintained sites, two in Lincoln and two in Beatrice, over 1.5 years to characterize TSS and PSD and to evaluate SAFL Baffle performance using the SHSAM model. Results showed large variability across sites and seasons. Median TSS ranged from 158 to 580 …