Engineering Commons^™

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

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

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.

Data For "Unified Vapor Pressure Correlations For Lanthanide And Actinide Chlorides: An In-Depth Statistical And Thermodynamic Approach", J. Marvin Torrie, Nicolas Marvin Christensen, Kyle Duke, Carlos Mejia, Larry Baxter, Devin Rappleye

ScholarsArchive Data

This submission contains machine readable data (.csv) for all data from the publication "Unified Vapor Pressure Correlations for Lanthanide and Actinide Chlorides: An In-depth Statistical and Thermodynamic Approach". It contains the data contained in all figures in the paper and its supplementary material except for the water vapor pressure data in Figures 1 and 2. In addition, this submission contains all the original vapor pressure measurements (241 sets) from the sources reviewed in the paper.  Sufficient information is provided that readers can identify the original sources of these data sets if needed.

Predicting Water Quality Using Quantum Machine Learning: The Case Of The Umgeni Catchment (U20a) Study Region, Jamal Al-Karaki, Muhammad Al Zafar Khan, Amjad Gawanmeh, Marwan Omar

All Works

The assessment of water quality has become increasingly vital for maintaining the ecological balance and ensuring public safety across global water systems. This study examines the application of Quantum Machine Learning (QML) techniques in a real-world setting to predict water quality in the U20A region of the Umgeni Catchment, Durban, South Africa. We implemented the Quantum Support Vector Classifier (QSVC) and Quantum Neural Network (QNN) on a field-collected dataset. Our results demonstrate that the QSVC is more practical to implement and yields superior performance, achieving 75 % accuracy with polynomial and radial basis function kernels. In contrast, the QNN encountered …

Raw Data Files Contributing To "Changes In Apoe And Timp-1 Expression Correlate With Outer Blood-Retinal Barrier Disruption In An In Vitro Model Of Retinal Aging", Elizabeth Vargis

Browse all Datasets

Age-related macular degeneration (AMD) is a leading cause of blindness worldwide. Unfortunately, the early stages of this disease are poorly understood, which has led to limited treatment options. Investigating normal changes in tissues eventually affected by AMD can further elucidate the mechanisms of disease progression and lead to novel therapeutic targets. The primary cell layer affected in AMD is the retinal pigment epithelium (RPE), which forms the outer blood-retinal barrier (oBRB). Beneath the RPE lies Bruch’s membrane, a proteinaceous layer that naturally thickens and stiffens with age. These changes to Bruch’s membrane are also implicated in RPE dysfunction and AMD …

Cs Tools - Stormwater Management Software (Version 6.5.0), Donald V. Chase

Drainage Design Tools

The CS Tools program is an outgrowth of research conducted by the University of Dayton for CON/SPAN Bridge Systems.

Data Set, R Scripts And Script Outputs For Manuscript: Manufacturing Systems: Characteristics And Dynamics, Alan J. Fitzmorris

Graduate Research Data

This file repository contains fifteen computer-generated datasets, two naturally occurring datasets, nineteen shipbuilding shop datasets, and sixty-one concrete plant datasets.  Each data set contains subdirectories associated with various aspects of the data analysis, including stationarity analysis, dynamic system analysis, and complexity analysis.  In each case, applicable R scripts are included.  The text file entitled “Directory_and_File_Names” depicts the directory structure and associated file names for a total of 225 directories encompassing 8008 files.

Data For: Optimizing Finite Structures To Suppress The Photonic Density Of States, Prakash Mishra, Sukhad Dnyanesh Joshi, Quintin A. Hatzis, Aditya Bahulikar, M. Cenk Gursoy, Rodrick Kuate Defo

Electrical Engineering and Computer Science - All Scholarship

We propose a topology-optimization framework for optimizing finite structures of arbitrary shape by combining density-based methods with level-set approaches. We first optimize regular polygonal structures to suppress the photonic density of states and find that the best performing polygon is consistent with a tiling of space with hexagonal unit cells. We next show that introducing cavities into hexagonal structures further suppresses the photonic density of states, particularly when the cavity is also hexagonal. Such a result would find application in the design of fiber-optic cables. We then describe an approach for optimizing arbitrary x-simple or y-simple designs that can recover …

Anonymized Survey Dataset On Road Safety Assessment During Construction Of Bus Rapid Transit (Brt) Corridors In Dar Es Salaam, Tanzania, Lorain Salufu

Open Data

This dataset contains anonymized survey responses collected for a study on road safety assessment during construction of the Dar es Salaam Bus Rapid Transit (BRT) Phase 3 corridor. The dataset includes responses from 400 participants, together with the survey. The data were collected to assess perceived safety conditions, adequacy of construction-phase safety measures, effectiveness of traffic diversions, and the effects of construction activities on road users and nearby communities. No personally identifiable information is included in the shared files.

Raw Data For The Manuscript "Silicon-Stabilized Three-Dimensional Covalent Networks In High Entropy Diborides", Michael Yeung, Reza Mohammadi

Chemistry Department Faculty Scholarship

Abstract for data:

Raw data for the journal publication, Silicon-stabilized three-dimensional covalent networks in high entropy diborides. ReadMe file provided.

Abstract for Journal publication: 

High entropy ceramics offer a pathway to stabilize unconventional chemistries beyond traditional alloying rules. We report the incorporation of silicon into an AlB₂-type high entropy diboride, Cr_0.2Nb_0.2Si_0.2Ta_0.2Ti_0.2B₂, despite silicon violating classical Hume-Rothery rules for alloying. Arc melting produced a phase-pure, chemically homogeneous structure, as confirmed by powder X-ray diffraction (pXRD) and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM–EDS). Silicon occupies …

Ansys Discovery And Fluent Files For Modeling A Hydrocyclone With Scco2 And Coal Fly Ash, Isaiah Morones, Catherine Brewer

Chemical & Materials Engineering: Datasets

No abstract provided.

Sustainable Paper Production From Date Palm And Reed Leaves Through The Valorization Of Agricultural Waste Products, Imane Belyamani, Alreem Alameri, Jacqueline Soghman

All Works

The environmental consequences of wood-based paper production, including greenhouse gas emissions, have accelerated the search for sustainable alternatives. This study investigates the use of reed and date palm fibers as eco-friendly raw materials for paper production, focusing on starch's influence on their thermal, structural, and mechanical properties. Reed fibers exhibited a higher pulp yield (58.2 %) and lower lignin content (7.8 %) compared to date palm fibers (55.9 % yield, 14.1 % lignin), contributing to papers with smoother textures and greater flexibility. The incorporation of starch into both fiber types resulted in notable performance improvements, though the effects were more …

Artificial Sense-Making Dataset, Jason A. Bengtson, John Sandstrom, Nathan Camp

NMSU Library: Datasets

No abstract provided.

Nazi Weapons: Bad People, Good Technology, Fabian Grabski

Undergraduate Research Symposium

This project explores the integration and historical significance of three iconic World War II-era German weapons: the V-2 rocket, the STG-44, and the MG-42. Each of these weapons helped revolutionized military technology in its own right, reshaping the battlefield dynamics and influencing future weapon design. The V-2 rocket, as one of the first long-range guided missiles, marked the dawn of modern missile technology, while the STG-44 is recognized as a precursor to the modern assault rifle, blending the characteristics of both submachine guns and rifles. The MG-42, with its high rate of fire and advanced design, set the standard for …

Polydopamine-Coated Magnetic Nanoparticles Data, William G. Pitt

ScholarsArchive Data

This data archive contains raw data and processed data related to research and development of magnetic nanoparticles that adhere to bacteria. This data is the foundation of data in the MS thesis of Bowen Houser, and publications and presentations related to that research effort. Polydopamine-coated magnetic nanoparticles are found to be very adhesive to gram-positive bacteria, and less adhesive to gram-negative bacteria. These data files contain information for S. aureus, S. epidermidis, S. mutans, E. coli, P. aeruginosa, and N. perflava. Some data include the kinetics of capture.

Data Release Of 5-Fluorouracil From Polylactic Acid Microparticles Containing Magnetic Nanoparticles, William G. Pitt

ScholarsArchive Data

This data archive contains raw data and processed data related to research and development of the release of the chemotherapy drug 5-fluororacil from microparticles of poly(lactic acid) which also contain superparamagnetic magnetite nanoparticles. This data is the foundation of data in the MS thesis of Tyler Green, and publications and presentations related to that research effort.

Reinforcement Learning Based Intelligent Optimisation For Bin Packing Problems: A Review, Nadia Dahmani, Amril Nazir, Ikbal Taleb, Syed M.Salman Bukhari

All Works

The convergence of Reinforcement Learning (RL) and Bin Packing Problems (BPP) is a critical field of study that has profound ramifications in logistics, manufacturing, computer, and retail industries. This paper thoroughly examines the progression from simple rule-based tactics to advanced Deep Reinforcement Learning (DRL) techniques in solving BPPs. By conducting a thorough review of 231 papers conducted between 2019 and 2024, we address and provide answers to important research inquiries, such as “To what extent has academic research explored the use of RL for BPP during this time frame?” and “Which specific areas of application and methodologies have been predominantly …

Artificial Intelligence In Waste Management Systems: Applications, Challenges, And Prospects, Imane Belyamani

All Works

Despite global recognition of the climate crisis, greenhouse gas emissions are projected to rise by 8.8 % by 2030, primarily due to inadequate planning, poor implementation, and insufficient financial support. While international initiatives such as the ’Waste to Zero’ coalition launched at the 28th Conference of the Parties to the UNFCCC (COP 28) highlight the urgency of advancing decarbonization and the circularity of waste systems, this review focuses on how artificial intelligence (AI) can accelerate that transformation. It systematically explores the role of AI in advancing waste management practices, with a focus on predictive analytics, route optimization, and machine learning-based …

Fall 2024 Computer Programming And Engineering Self-Efficacy Survey Data, Mary Benjamin

Michigan Tech Research Data

This dataset was collected as part of a research study examining the impact of automated code critiquers on students’ programming and engineering self-efficacy in first-year engineering courses. The study involved pre- and post-surveys administered to students enrolled in ENG1101: Introduction to Engineering during Fall 2024 at Michigan Technological University. The research aims to understand how exposure to automated feedback tools, such as WebTA, influences confidence, persistence, and perceived competencies.

Modeling Social Isolation: A Data-Driven Index Function Design And Implementation, Jeremis N. Morales Morales, Carmen Caiseda, Phyllis Muniu, Joshua Atsu, Folashade B. Agusto

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Abdominal Ultrasound Image Dataset For Organ Classification And Disease Detection, Sifat Zina Karim

Research Data

This is a dataset of Ultrasound (US) images of abdominal organs. US imaging is widely accessible and a very common diagnostic tool, as it is non-invasive and does not involve radiation risk. This dataset was curated solely for research in deep learning, with potential applications in supervised, semi-supervised, and unsupervised learning to support disease detection in resource-constrained settings.

The dataset comprises 5,468 unique images of different abdominal organs, namely: Abdominal Aorta (0), Gallbladder (1), Hepatic Vein (2), Kidneys (3), Liver (4), Ovaries (5), Pancreas (6), Portal Vein (7), Spleen (8), and the Urinary System (9), which includes the Urinary Bladder, …

Reliability Targeted Snow Loads And Winter Wind Parameters For Locations Outside Of The Conterminous United States, Brennan L. Bean, Nicholas Brimhall, Bikram Bhusal, Marc Maguire, Maha Moussa

Browse all Datasets

The national building standard ASCE 7 moved to reliability-targeted snow loads (RTSLs) in the 2022 version. This necessitates the development of RTSLs for international locations. This repository contains the data and code needed to produce RTSLs and Winter Wind Parameters for locations outside of the Conterminous United States (OCONUS). It relies on annual maximum snow loads provided in a separate data release (see Brimhall et al. 2025).

Low Head Dam Fatalities Data 1900 To August 2025, Rollin H. Hotchkiss, Edward William Kern, John Guymon, Paige A. Gordichuk

ScholarsArchive Data

This dataset documents fatalities at low head dams in the United States between 1900 and August 2025. The records were compiled between 2012 and 2025 by research assistants at Brigham Young University under the direction of Dr. Rollin Hotchkiss. Data were incorporated into the database from Dr. Bruce Tschantz, Charlie Walbridge of the American Whitewater Association, public submissions through a “Report an Incident” form, and publicly available sources, including newspaper archives and public records. Originally stored in a MySQL database and later transferred to Google Sheets, the August 2025 version was exported to Excel. The purpose of the dataset is …

Hourly Simulated Power Production Data With Snow Loss Model At Existing Utility-Scale Pv Sites (>5 Mw) In The U.S. Eastern Interconnection In 2018, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Project Summary: We ran PySAM power production simulations for utility-scale (>5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2018. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory's Utility-Scale Solar 2024 Edition dataset. See 2018_PV_existing_site_metadata.csv file for individual site metadata.

Hourly Simulated Power Production Data With No Snow Loss Model At Existing Utility-Scale Pv Sites (>5 Mw) In The U.S. Eastern Interconnection In 2014, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Project Summary: We ran PySAM power production simulations for utility-scale (>5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2014. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory's Utility-Scale Solar 2024 Edition dataset. See 2014_PV_existing_site_metadata.csv file for individual site metadata.

Hourly Simulated Power Production Data With No Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2014, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2014 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory's Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata

Hourly Simulated Power Production Data With No Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2021, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2021 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory's Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata

Hourly Simulated Power Production Data With No Snow Loss Model At Queued Utility-Scale Pv Sites Simulated As Single-Axis Tracking Systems In The U.S. Eastern Interconnection For Weather Year 2022, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Using 2022 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory's Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata

Hourly Simulated Power Production Data With Snow Loss Model At Existing Utility-Scale Pv Sites (>5 Mw) In The U.S. Eastern Interconnection In 2022, Shelbie Wickett, Ana Dyreson

Simulated Solar Capacity Including Snow Cover in the Eastern U.S.

Project Summary: We ran PySAM power production simulations for utility-scale (>5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2022. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory's Utility-Scale Solar 2024 Edition dataset. See 2022_PV_existing_site_metadata.csv file for individual site metadata.