Digital Commons Network^™

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

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

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

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

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

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

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.

Male Steller Sea Lion (Eumetopias Jubatus) Skull, Jade A. Mells, Nicholas D. Burchett, Amy Hirons

Hirons Field Techniques

No abstract provided.

Using Art To Understand Children's Perceptions Of Covid-Era Schooling, Katrina Bartow Jacobs, Kali Stull

IALS Journal

This study explores how elementary-aged children (K–5) made sense of their Covid-era schooling experiences at Falk Laboratory School. Using an arts-based methodology combining drawing and narrative reflection, researchers collected 232 student artworks and 225 narratives. Findings revealed that older children referenced Covid-related experiences more frequently than younger children, that Covid held similar emotional significance to other school experiences, and that children's responses included both positive and negative emotions. A notable subset of students, particularly some neurodiverse learners, expressed positive feelings about remote learning, smaller groups, and masking. The study highlights the value of arts-based research in centering children's voices and …

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.

Supporting Data – Urban Stream, Cardinal Court, Isu, Normal, November 9, 2023 To May 1, 2025, Eric Wade Peterson, Ava Miller

Faculty Publications - Geography, Geology, and the Environment

Between November 9, 2023 to May 1, 2025, water samples were collected upstream and downstream along a segment of a stream adjacent to Cardinal Court on the Illinois State University campus. At each location, samples were collected at the surface. In-situ measurements of Dissolved Oxygen, Specific Conductance, and Temperature were recorded with a YSI 85. Anion samples were analyzed using a Ion Chromatograph for fluoride (F^-), chloride (Cl^-), nitrate as nitrogen (NO3-N), phosphate (PO₄^3-), and sulfate (SO₄^2-). The available dataset provides the recorded field parameters and the analyzed ion concentrations.

Developing Ecosocial Literacy / Transforming Ecosocial Leadership: A Curriculum Research & Development Project, Chris Zorn, Lois A. Yamauchi, Madiha Jamil

IALS Journal

This case study examines the Global Leadership Laboratory (GLL), a yearlong high school leadership course at University Laboratory School in Hawaiʻi. The curriculum integrates transformative learning and contemplative practices to promote student voice, self-awareness, leadership skills, and personal agency. Through interviews, observations, and student artifacts, the study found that reflective journaling, dialogue, contemplative practices, and transformative learning activities supported the development of authentic student voice and perspective transformation, although outcomes varied by classroom conditions and student readiness.

The Social And Cultural Challenges Experienced By Children With Send Through Quasi-Inclusion Practices In Two Mainstream Primary Schools In Postcolonial Guyana, Lidon Lashley, Clevelon Gordon

IALS Journal

This ethnographic study investigates the sociocultural experiences of 36 children with SEND and two non-SEND peers in two rural mainstream primary schools in Guyana. Through interviews, observations, and situational analysis, the study explores how ableism, colonial legacies, prejudice, poverty, linguistic barriers, and inadequate educational support shape the experiences of children with SEND. Findings reveal persistent stigmatization, discrimination, marginalization, exclusion, and "fated failure" discourses that negatively affect learning, participation, agency, and wellbeing. The study concludes that teachers require greater support, training, and specialist resources to foster genuine inclusion within Guyana's mainstream schools.

Students’ Perceptions At The University Of Puerto Rico Secondary School Regarding Cellphone Use In The School Environmen, Nicolás Ramos, Nydiaam Vilanova

IALS Journal

This mixed-methods study investigates students’ perceptions of cellphone use at the University of Puerto Rico Secondary School. Data were collected from 133 students through a structured electronic survey examining phone ownership, usage patterns, emotional responses, parental regulation, and opinions regarding cellphone restrictions in schools. Results indicate that most students perceive their cellphone use as appropriate, recognize both educational and social benefits, and oppose complete bans while supporting responsible use and guided autonomy. The findings suggest that schools should emphasize digital citizenship, self-regulation, and balanced technology use rather than punitive restrictions.

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 …

Terrorism And Misperceptions: Evidence From Europe, K. Peren Arin, Umair Khalil, Deni Mazrekaj, Marcel Thum

All Works

How does exposure to Islamist terrorism change perceptions about Muslims and immigrants? We conducted a large-scale survey that measures misperceptions towards minority groups in four European countries. Our results show that terror attacks in the past increased misperceptions of the share of Muslims and immigrants. We also contend that this increase in misperceptions is particularly large and significant for lower-educated respondents and people from regions with a low share of the foreign population. Given that misperceptions are higher on average in regions with a large share of foreigners, terror attacks make misperceptions across different regions converge.

Foreword By Guest Editor, Katrina Bartow Jacobs, Phd

IALS Journal

No abstract provided.

The Voices Of Play- Understanding Children’S Perspectives Of Naturalized And Forested Outdoor Play Environments, Kimberly Squires, Kim Barton, Madi Stubbs, Mandy English

IALS Journal

is qualitative participatory study explored young children's perspectives of naturalized and forested outdoor play environments at an early learning laboratory school in Ontario, Canada. Drawing on the Mosaic Approach, photo-elicitation, and the Reggio Emilia concept of the hundred languages of children, researchers invited preschool children to communicate their perspectives through photography, drawing, and discussion. Findings revealed that both naturalized and forested environments supported meaningful connections with nature, although children engaged with each setting in distinct ways. Forested environments encouraged broader and more action-oriented interactions with natural materials, while naturalized environments fostered more diverse and specific connections with environmental features. The …

Students’ Conceptions Of The Future: Participatory Co-Research And Teaching Experiment, Anna Veijola, Tuukka Tomperi

IALS Journal

This study examines upper secondary students’ conceptions of the future through a participatory teaching and research experiment conducted in a philosophy course at the University of Jyväskylä Teacher Training School. Students collaboratively created short films imagining the world in 2043 and wrote reflective essays about the ethical and philosophical issues represented in their films. Using the framework of Futures Consciousness, the researchers analyzed themes related to time perspective, agency, openness to alternatives, systems thinking, and concern for others. Findings revealed that students expressed both utopian and dystopian visions rooted in contemporary global concerns such as climate change, inequality, technological development, …

Experimental Data: Sloshing In A Circular Tank, Stuart Colville, Francesco Gambioli, Deborah Greaves, Yeaw Chu Lee

Faculty of Science and Engineering Datasets

This experimental dataset was generated as part of a PhD research project on liquid sloshing for next-generation aircraft fuel tank applications (EP/W522223/1). It comprises three distinct experimental campaigns designed to characterise sloshing behaviour under a range of controlled dynamic conditions with water-air. A circular tank under forced horizontal excitation. A circular tank under forced vertical excitation. A circular tank under high-acceleration vertical excitation. Together, these campaigns provide a comprehensive set of measurements capturing fluid response in a circular tank across varied excitation modes and acceleration regimes. The dataset is intended to support further research, model validation, and the development of …

Kernel Density Estimate (Kde) Surfaces Of Wintering Tidal Marsh Birds Along The Mississippi Gulf Coast, Carlos Ramirez-Reyes, Kristine O. Evans, Mark S. Woodrey, Rachel V. Anderson, Jared Feura, Landon R. Jones, Raymond B. Iglay

Research Data

This dataset accompanies the article Spatial patterns of habitat use of wintering tidal marsh birds along the Mississippi Gulf Coast and includes kernel density estimate (KDE) raster layers describing spatial patterns of bird abundance and community richness derived from winter bird surveys. The study examined landscape features associated with the occurrence and spatial distribution of eight tidal marsh bird species during the non-breeding season along the Mississippi Gulf Coast.

Using field observations collected along fixed transects, the analysis evaluated differences between occupied and unoccupied transects, associations between bird occurrence and landscape-level predictors at ecologically relevant spatial scales, and species co-occurrence …

Extract_Text_From_Pdfs, Manish Rami

Software

This file uses two programs to extract text from pdfs. The text then can be analyzed for various purposes.

Terrence Dean, Mark Naison, Steven Payne, Pastor Crespo Jr., Akilah Shedrick

Oral Histories

No abstract provided.

Marti Zuckrow - Part 1, Mark Naison, Steven Payne

Oral Histories

No abstract provided.

Marti Zuckrow - Part 2, Mark Naison, Steven Payne

Oral Histories

No abstract provided.

Joellen Eisenman Sgueglia, Mark Naison, Steven Payne

Oral Histories

No abstract provided.

Uconn Lco/Gr Battery Fast Charging Dataset, Sina Navidi, Sourav Das, Benjamin Nowacki, Pranav Shrotriya, Jun Xu, Chao Hu

REIL Datasets

This dataset comprises 76 Powerstream LiR 2032 lithium cobalt oxide/graphite (LCO/Gr) coin cells used to study Coulombic efficiency and long-term degradation under fast charging conditions. The dataset includes 40 cells tested using SOC-sweep experiments and 36 cells evaluated using benchmark fast charging protocols. SOC-sweep experiments were conducted at four target SOH levels (100%, 90%, 80%, and 70%) and across multiple charging C-rates (1.5C–3.5C) to characterize the dependence of Coulombic efficiency on SOC, C-rate, and SOH. Benchmark tests were designed to assess protocol-dependent degradation and consisted of repeated blocks of charge-discharge cycling followed by reference performance tests (RPTs) to measure capacity. …

Datasets For Response Of A Liquid Water Cloud To In Situ Hygroscopic Seeding, James Simmons

Michigan Tech Research Data

We have performed experiments in the Michigan Tech Pi Chamber to assess the response of a steady-state, liquid water cloud to in situ injection of a hygroscopic powder. Three materials were tested: jet-milled NaCl, a newly developed NaCl-TiO2 core-shell material, and Arizona test dust as a non-hygroscopic control. Injection of the hygroscopic materials resulted in an increase of the local liquid water content, stimulating formation of droplets up to 60 microns in diameter. Upon injection of the powders, the pre-existing cloud in the chamber collapsed.