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Articles 331 - 360 of 150088

Full-Text Articles in Physical Sciences and Mathematics

Commissioning And Performance Characterization Of An Elevator Loading System For The Ucnτ+ Magneto-Gravitational Trap, Alexander Komives, Et Al. Sep 2026

Commissioning And Performance Characterization Of An Elevator Loading System For The Ucnτ+ Magneto-Gravitational Trap, Alexander Komives, Et Al.

Physics & Astronomy Faculty publications

We report the first commissioning with ultracold neutrons (UCN) of an elevator-based loading system for the UCNτ magneto-gravitational neutron trap at Los Alamos Neutron Science Center. The system replaces the previous trap-door geometry with a moving bin designed to transfer UCN from UCN guide height into the open trap while reducing their kinetic energy through an adiabatic expansion of the accessible volume. UCN cutoff energy scans, direct leakage measurements, and variable bin-hold cycle measurements were used to characterize the incident spectrum and the loading losses. Successive sealing modifications increased the effective bin population lifetime from 26.69 ± 0.62 to 47.64 …

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Re: Butte Priority Soils Operable Unit Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No. 46 – Missoula Mine, Mike Mcanulty Sep 2026

Re: Butte Priority Soils Operable Unit Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No. 46 – Missoula Mine, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Butte Priority Soils Operable Unit Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No 135 – Washoe Sampling Works, Mike Mcanulty Sep 2026

Butte Priority Soils Operable Unit Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No 135 – Washoe Sampling Works, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Ai-Assisted Scenic Route Recommendation Using Street-Level Imagery And User Preference Modeling, James Slagter Sep 2026

Ai-Assisted Scenic Route Recommendation Using Street-Level Imagery And User Preference Modeling, James Slagter

Research from the Berry Summer Thesis Institute, 2026

This project showcases the development and implementation of an artificial intelligence framework trained from a large dataset of street-level images to categorize new images with similar attributes.  The framework is implemented into an application to be used as a mobile navigation software.  The application is constructed using three main languages: Dart, Python, and Java, and uses several SDKs including Google Maps, Firebase, geolocators, shared preferences, and other Flutter resources.  The framework is constructed using a main artificial intelligence model, TensorFlow, trained from hundreds of Google Maps street view images and personally collected images.  The TensorFlow model is provided these images, …

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Variability In Nutrient And Carbon Cycling Of Constructed Marshes, Alyssa Leclaire, Jenny Davis, Molly Bost, David De La Garza Sep 2026

Variability In Nutrient And Carbon Cycling Of Constructed Marshes, Alyssa Leclaire, Jenny Davis, Molly Bost, David De La Garza

School of Earth, Environmental, & Marine Sciences Faculty Publications

Salt marshes provide valuable ecosystem services, including filtering nutrients and trapping sediments from the water column, but are increasingly threatened by sea-level rise and coastal development. Constructed marshes offer a potential pathway to offsetting marsh loss, but the extent to which they can replace the ecosystem services provided by mature natural marshes is not well understood. Using a chronosequence of constructed marshes (1, 21, and 44 years old) and a natural reference marsh (>100y old) in Beaufort, NC, we assessed the development of plant communities, sediment characteristics, and nutrient and carbon cycling over time. We compared aboveground biomass, surface …

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Butte Priority Soils Operable Unit Draft Final Reclamation Improvement Field Sampling And Investigation Plan: Bres No. 57 – Little Mina-1, Mike Mcanulty Sep 2026

Butte Priority Soils Operable Unit Draft Final Reclamation Improvement Field Sampling And Investigation Plan: Bres No. 57 – Little Mina-1, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Butte Priority Soils Operable Unit Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No. 11 – Magna Charta Lessee Dumps, Mike Mcanulty Sep 2026

Butte Priority Soils Operable Unit Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No. 11 – Magna Charta Lessee Dumps, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Butte Priority Soils Operable Unit Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No. 129 – Heaney Dump, Mike Mcanulty Sep 2026

Butte Priority Soils Operable Unit Draft Final Insufficiently Reclaimed Sites Field Sampling And Investigation Plan: Bres No. 129 – Heaney Dump, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Butte Priority Soils Operable Unit Draft Final Reclamation Improvement Field Sampling And Investigation Plan: Bres No. 160s – Syndicate Pit Dumps, Mike Mcanulty Sep 2026

Butte Priority Soils Operable Unit Draft Final Reclamation Improvement Field Sampling And Investigation Plan: Bres No. 160s – Syndicate Pit Dumps, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Butte Priority Soils Operable Unit Draft Final Reclamation Improvement Field Sampling And Investigation Plan: Bres No. 180 – Tullamore Dumps, Mike Mcanulty Sep 2026

Butte Priority Soils Operable Unit Draft Final Reclamation Improvement Field Sampling And Investigation Plan: Bres No. 180 – Tullamore Dumps, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Epistemic Resilience In Ai-Driven Innovation, James C. Ryan, Massimiliano Cappuccio, Effrosyni Georgiadou, Alessandro Lanteri Sep 2026

Epistemic Resilience In Ai-Driven Innovation, James C. Ryan, Massimiliano Cappuccio, Effrosyni Georgiadou, Alessandro Lanteri

All Works

Artificial intelligence (AI) has become an integral component of innovation infrastructure, facilitating information retrieval, knowledge recombination, and decision support. While these applications accelerate innovation cycles, they simultaneously obscure evidential provenance, compromise output reliability, and diffuse accountability when algorithmic insights fail. To address these vulnerabilities, this paper introduces the concept of epistemic resilience, defined as an organizational and ecosystem capability to preserve, adapt, and restore trustworthy knowledge processes amid technological disruption, uncertainty, and epistemic risk. Synthesizing literature across innovation management, organizational learning, knowledge management, social epistemology, research integrity, and human–AI collaboration, this study conceptualizes AI-driven innovation as a sociotechnical knowledge process …

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2026 Report On The State Of Great Salt Lake Social Science, Creed Jones, Avyrlie Smith, Shae Barber, Stacia Ryder, Mufti Nadimul Quamar Ahmed, Georgie Corkery, Jennifer Givens, Anna Mcentire, Carla Trentelman, Jessica Ulrich-Schad, Kirsten Vinyeta, Bryn Watkins Sep 2026

2026 Report On The State Of Great Salt Lake Social Science, Creed Jones, Avyrlie Smith, Shae Barber, Stacia Ryder, Mufti Nadimul Quamar Ahmed, Georgie Corkery, Jennifer Givens, Anna Mcentire, Carla Trentelman, Jessica Ulrich-Schad, Kirsten Vinyeta, Bryn Watkins

Publications

Great Salt Lake (GSL) faces rapid decline that presents more than just a hydrological risk; it poses an existential social hazard. As water levels decline, ecosystems, economies, cultures, and societies face irreversible harm. Since the lake reached its lowest levels in 2022, this issue has specifically gained increased attention in Utah and beyond. Given both the degree to which human consumption contributes to the problem, and the potential risks that the drying of the lake poses for community health, social science research is a crucial for informing successful water management policies and mitigating impacts. The purpose of this report is …

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Readme Template For Geospatial Data, Alyssa Renteria Sep 2026

Readme Template For Geospatial Data, Alyssa Renteria

Library Faculty Research

A readme file provides descriptive information about a dataset, file(s), or software. The goal is to ensure that the files and data can be correctly interpreted by your future self or others when sharing or publishing data, code, or software.

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Agentic Ai For Autonomous Marketing: Taxonomy, Benchmark, And An Open-Source Agent, Prashidda Thapa, Shraddha Khadka, Pragyan Sharma, Ana Rai Sep 2026

Agentic Ai For Autonomous Marketing: Taxonomy, Benchmark, And An Open-Source Agent, Prashidda Thapa, Shraddha Khadka, Pragyan Sharma, Ana Rai

Student Publications

Marketing automation is moving beyond rule-based systems and prompt-driven generative tools toward agentic AI: large language model (LLM) based agents that plan, act, and adapt under high-level objectives. Existing analyses are largely conceptual and commercial platforms are proprietary, leaving the community without reproducible baselines. We contribute three artifacts. First, a compact taxonomy organized around an augmentation–automation-autonomization continuum and a Perceive–Reason–Act(PRA)cycle that distinguishes autonomous agents from rule-based automation. Second, MarketingAgent, an open-source ReAct agent with six tools spanning SQL access, RFM segmentation, XGBoost churn prediction, campaign and email generation, and budget allocation. Third, the Marketing Agent Benchmark (MAB), a 15-task suite …

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Do Ensemble Models Always Win? A Comparative Machine Learning Evaluation For Financial Time-Series Prediction, Shraddha Khadka, Prashidda Thapa, Pragyan Sharma, Shreya Silwal Sep 2026

Do Ensemble Models Always Win? A Comparative Machine Learning Evaluation For Financial Time-Series Prediction, Shraddha Khadka, Prashidda Thapa, Pragyan Sharma, Shreya Silwal

Student Publications

Equal-weighted ensembling is often treated as a default upgrade over individual machine learning models. We test this assumption on one-day-ahead stock-price prediction across five sector diversified U.S. assets (2015–2024) by comparing Random Forest (RF), Support Vector Regression (SVR), Long Short-Term Memory (LSTM), and their equal-weighted average under identical features, preprocessing, and chronological splits. Pooled across assets, LSTM attains the lowest test-set RMSE (17.70), SVR is statistically tied with LSTM under the Diebold and Mariano test (𝑝 = 0.494), the equal-weighted ensemble is third (18.13), and RF is last (20.33); SVR beats the ensemble at 𝑝 = 0.001 (Bonferroni-significant) while LSTMbeats …

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Allochthonous Particulate Organic Carbon In Blue Carbon Ecosystems: Implications For Accounting, Stability, And Policy, Anirban Akhand, Inés Mazarrasa, Stacey M. Trevathan-Tackett, K. M.G. Mostofa, Abhra Chanda, Hongbin Liu, Hiroshi Sakugawa, Si Liang Li, Cong Qiang Liu, Catherine E. Lovelock, Paul Lavery, Hilary Kennedy, Peter I. Macreadie Sep 2026

Allochthonous Particulate Organic Carbon In Blue Carbon Ecosystems: Implications For Accounting, Stability, And Policy, Anirban Akhand, Inés Mazarrasa, Stacey M. Trevathan-Tackett, K. M.G. Mostofa, Abhra Chanda, Hongbin Liu, Hiroshi Sakugawa, Si Liang Li, Cong Qiang Liu, Catherine E. Lovelock, Paul Lavery, Hilary Kennedy, Peter I. Macreadie

Research outputs 2022 to 2026

Blue carbon ecosystems (BCEs) store a significant amount of organic carbon (OC) in their soils, including OC sequestered by other ecosystems and transported into these ecosystems, referred to as allochthonous OC. This study reviews the state-of-the-art knowledge on the abundance and sources (including still unexplored ones) of allochthonous particulate organic carbon (POC) and reviews the ways allochthonous POC is managed under the current blue carbon policy frameworks for carbon benefits accounting in blue carbon restoration and conservation projects. Based on a review of 102 studies, we find that 56 ± 25% of the soil organic carbon (SOC) deposits in BCEs …

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Waste Streams From Next Generation Molten Salt Reactors: The Challenge Of Creating An Insoluble Ceramic For Chloride Salt Waste, Alevtina A. Maksimova, Jake W. Amoroso, Matthew Page, Gregory Morrison, Hans Conrad Zur Loye Sep 2026

Waste Streams From Next Generation Molten Salt Reactors: The Challenge Of Creating An Insoluble Ceramic For Chloride Salt Waste, Alevtina A. Maksimova, Jake W. Amoroso, Matthew Page, Gregory Morrison, Hans Conrad Zur Loye

Faculty Publications

Molten salt reactors (MSRs) design development is of interest to many research groups and companies. Waste management for MSRs is one of the most important issues that needs to be resolved due to its impact on environmental safety, primarily via the dissolution of radionuclides in water. Furthermore, the waste treatment strategy will have a significant influence on the operating cost of MSRs, which is why a reliable process for the immobilization, transportation, storage and disposal of MSR waste must be addressed. This work presents a new approach for the immobilization of chloride salts from molten salt reactors in stable oxyhalide …

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Enhancing Programming Productivity For Individuals With Adhd Through Generative Artificial Intelligence: An Inductive Analysis, Lionel Mew Sep 2026

Enhancing Programming Productivity For Individuals With Adhd Through Generative Artificial Intelligence: An Inductive Analysis, Lionel Mew

School of Professional and Continuing Studies Faculty Publications

Attention-deficit/hyperactivity disorder (ADHD) significantly impacts computer programmers through challenges in sustained attention, executive functioning, and organizational skills. While traditional intervention strategies have shown varying degrees of success, the emergence of generative artificial intelligence (AI) presents novel opportunities to address ADHD-related programming challenges. This paper presents an inductive analysis synthesizing current research on ADHD's effects on programming, traditional productivity enhancement techniques, and the potential of generative AI tools. Through examination of recent literature and field studies, we propose that generative AI can serve as a transformative intervention by providing personalized cognitive support, reducing executive function demands, and enhancing code generation efficiency. …

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Which Factors Are Most Important For Understanding Neighborhood-Scale Electrification Transitions In New York City, And How Do These Factors Interact Within Urban Energy Systems?, Aaryan Nair Sep 2026

Which Factors Are Most Important For Understanding Neighborhood-Scale Electrification Transitions In New York City, And How Do These Factors Interact Within Urban Energy Systems?, Aaryan Nair

Publications and Research

Building electrification has emerged as a central strategy for reducing greenhouse gas emissions from urban areas, yet its implementation remains uneven across cities due to differences in buildings, infrastructure, and local conditions. This literature review examines the factors that influence neighborhood-scale electrification transitions in New York City and explores how these factors interact within urban energy systems. Drawing on research from building science, energy systems, infrastructure planning, and sustainability transitions, the paper identifies five recurring categories of influence: building characteristics, demand characteristics, infrastructure conditions, planning and investment capacity, and socioeconomic conditions. The review finds that building age, typology, density, and …

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Restoring Linguistic Grounding In Vla Models Via Train-Free Attention Recalibration, Ninghao Zhang, Bin Zhu, Shijie Zhou, Jingjing Chen Sep 2026

Restoring Linguistic Grounding In Vla Models Via Train-Free Attention Recalibration, Ninghao Zhang, Bin Zhu, Shijie Zhou, Jingjing Chen

Research Collection School Of Computing and Information Systems

Vision-Language-Action (VLA) models enable robots to perform manipulation tasks directly from natural language instructions and are increasingly viewed as a foundation for generalist robotic policies. However, their reliability under Out-Of-Distribution (OOD) instructions remains underexplored. In this paper, we reveal a critical failure mode in which VLA policies continue executing visually plausible actions even when the language instruction contradicts the scene. We refer to this phenomenon as linguistic blindness, where VLA policies prioritize visual priors over instruction semantics during action generation. To systematically analyze this issue, we introduce ICBench, a diagnostic benchmark constructed from the LIBERO dataset that probes language–action coupling …

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Facevalue: Exploring Real-Time Self-View Overlays To Prompt Meaning-Oriented Self-Awareness In Remote Meetings, Gun Woo (Warren) Park, Anthony Tang, Fanny Chevalier Sep 2026

Facevalue: Exploring Real-Time Self-View Overlays To Prompt Meaning-Oriented Self-Awareness In Remote Meetings, Gun Woo (Warren) Park, Anthony Tang, Fanny Chevalier

Research Collection School Of Computing and Information Systems

In remote video meetings, visual non-verbal cues, such as facial expressions or head movements, are seen continuously but often only partially. This increases ambiguity compared to in-person settings and can cause misinterpretation or misalignment between intended and perceived meaning. Motivated by communication theories, we designed FaceValue, a technology probe that augments the self-view with private, real-time overlays. These overlays are subtle, suggestive prompts intended to help attendees reflect on how their cues might be interpreted by others. To invite personal interpretation, FaceValue avoids behavioral labeling and instead aims to support meaning-oriented self-awareness: recognizing when visible cues may unintentionally (mis)communicate intent. …

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Revised Draft Final Annual Operations And Maintenance (O&M) Report: Butte Treatment Lagoon (Btl) System – 2025, Pioneer Technical Services, Inc. Sep 2026

Revised Draft Final Annual Operations And Maintenance (O&M) Report: Butte Treatment Lagoon (Btl) System – 2025, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Final 2023 Unreclaimed Sites Sampling: Ur-42 Site Evaluation Summary Report, Pioneer Technical Services, Inc. Sep 2026

Final 2023 Unreclaimed Sites Sampling: Ur-42 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Monthly Progress Report Butte Priority Soils Operable Unit Consent Decree Partial Remedial Design/Remedial Action And Operation And Maintenance - September 2026, Atlantic Richfield Company Sep 2026

Monthly Progress Report Butte Priority Soils Operable Unit Consent Decree Partial Remedial Design/Remedial Action And Operation And Maintenance - September 2026, Atlantic Richfield Company

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Ecu-Malnett V2, Matthew G. Gaber, Mohiuddin Ahmed, Michael N. Johnstone Sep 2026

Ecu-Malnett V2, Matthew G. Gaber, Mohiuddin Ahmed, Michael N. Johnstone

Research Datasets

ECU-MALNETT (ECU MALware NETwork Traffic) is a real world, reproducible dataset of labeled benign and malicious network flows built from the Peekaboo execution corpus. Peekaboo runs evasive malware with dynamic binary instrumentation and records raw host-level PCAPs while granting full Internet access, yielding noisy, real-world captures with background OS activity and concurrent processes. To derive trustworthy labels from these traces, we apply Construct, a baseline aware, zero-trust labeling framework. Construct first ingests a baseline capture to establish reference sets (DNS qnames, HTTP hosts, TLS SNIs, and socket endpoints) and grows a conservative benign IP pool only via whitelisted DNS resolutions. …

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From Withdrawal To Impact: Smu Libraries’ Book Rehoming Initiatives, Kai Leong Heng, Eng Ling Lynn Yeo Sep 2026

From Withdrawal To Impact: Smu Libraries’ Book Rehoming Initiatives, Kai Leong Heng, Eng Ling Lynn Yeo

Research Collection Library

Academic libraries are no strangers to large-scale deselection exercises. Driven by space constraints, evolving curricula, and the shift towards digital resources, the question is no longer whether to withdraw print materials, but what comes next. In the past year, SMU Libraries explored a different answer: instead of recycling withdrawn books, could we reimagine their next chapter, and rehome them to create meaningful impact for the community?

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Governing Agentic Ai: The Human Values Alignment Framework (Hvaf-A) As A Policy Tool, Mousa Al-Kfairy Sep 2026

Governing Agentic Ai: The Human Values Alignment Framework (Hvaf-A) As A Policy Tool, Mousa Al-Kfairy

All Works

Agentic artificial intelligence (AI) systems—software that plans, acts, and decides without step-by-step human approval—are already deployed in finance, healthcare, recruitment, and public services. They differ from earlier AI in one critical way. They do not produce outputs for a human to accept or reject. They take actions. Those actions may be irreversible. They may affect people who never used the system. Existing governance frameworks were not designed for this. Current alignment approaches—including reinforcement learning from human feedback, constitutional AI, and preference aggregation—assume that a well-aligned system satisfies what users ask for. This paper argues that the assumption fails in agentic …

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Individualized Bayesian Inference Identifies Novel Genetic Variants For Parkinson's Disease, Jin Ren, Yasaman J. Soofi, Md Asad Rahman, Qing Lu, Jinling Liu Sep 2026

Individualized Bayesian Inference Identifies Novel Genetic Variants For Parkinson's Disease, Jin Ren, Yasaman J. Soofi, Md Asad Rahman, Qing Lu, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Parkinson's disease (PD) is a complex neurodegenerative disorder with a significant genetic component. While genome-wide association studies (GWAS) have been instrumental in identifying genetic variants associated with PD, the reliance on large sample sizes and population-level analyses may overlook variants with lower minor allele frequencies or individual-specific relevance. Individualized Bayesian Inference (IBI) offers a promising method to complement GWAS by identifying and prioritizing candidate genetic markers at both the individual and patients-like-me subgroup levels. This study evaluates the application of IBI to PD genetics, using GWAS as a baseline for comparison. We analyzed genetic data from the Fox Insight online …

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Preliminary Data: Old Trails Fire--Field Reconnaissance (Rpd1195), Rapid, University Of Washington Sep 2026

Preliminary Data: Old Trails Fire--Field Reconnaissance (Rpd1195), Rapid, University Of Washington

Spokane Wildfire Academic Consortium Repository

The .ZIP file contains preliminary field reconnaissance findings from the Old Trails Fire in Spokane, Washington, including geospatial datasets and the source code used to support the project's interactive web map. The data and observations reflect work completed through September 4 and should be considered preliminary. As additional analysis and information become available, updates will be published as new records in the Wildfire Consortium Repository.

Access the interactive map: https://designsafe-ci.github.io/rapid-fire-field-reconnaissance/

Access the DesignSafe-CI rapid-fire-field-reconnaissance GitHub repository: https://github.com/DesignSafe-CI/rapid-fire-field-reconnaissance/

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Learning 1-Bit Lidar-Based Localization With Auxiliary Objective, Kaijie Yin, Zhiyuan Zhang, Tian Gao, Wentao Zhu, Cheng-Zhong Xu, Hui Kong Sep 2026

Learning 1-Bit Lidar-Based Localization With Auxiliary Objective, Kaijie Yin, Zhiyuan Zhang, Tian Gao, Wentao Zhu, Cheng-Zhong Xu, Hui Kong

Research Collection School Of Computing and Information Systems

6-DoF LiDAR-based localization is a fundamental capability for autonomous systems operating in large-scale outdoor environments. Many deep-learning-based localization methods have achieved promising performance so far. However, as one of the always-on modules competing for limited on-board computational resources, the localization module is expected to consume only a small portion of the overall compute budget. Most existing learning-based methods are still too heavy for this purpose. In contrast, binary neural networks (BNNs) offer an appealing solution, but the 1-bit compression causes severe information loss and performance drop. In this paper, we address this challenge by proposing Binarized LiDAR-based Localization (BiLoc), the …

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