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From Assembly Lines To The Open Road: Predicting Rare Events In Autonomous Systems, Ruwan Wickramarachchi

Publications

In the age of embodied AI and smart automation, autonomous agents are increasingly deployed in high-stakes, real-world environments. Ensuring the robustness and resilience of these systems in the face of rare but critical failure events is essential for their safe and reliable operation. Accurate forecasting of such rare events is particularly crucial, as a single overlooked anomaly can lead to catastrophic consequences. In manufacturing, for instance, unplanned downtime due to rare failures costs industries over \$50 billion annually, with sectors like automotive losing more than \$2 million per hour—even with preventive maintenance systems in place.

However, the extreme rarity and …

Correction: Identification Of A Fusobacterial Rna-Binding Protein Involved In Host Small Rna-Mediated Growth Inhibition, Pu-Ting Dong, Mengdi Yang, Jie Hu, Lujia Cen, Peng Zhou, Difei Xu, Peng Xiong, Jiahe Li, Xuesong He

Faculty, Staff and Student Publications

No abstract provided.

A Conditional Point Cloud Diffusion Model For Deformable Liver Motion Tracking Via A Single Arbitrarily-Angled X-Ray Projection, Jiacheng Xie, Hua-Chieh Shao, Yunxiang Li, Shunyu Yan, Chenyang Shen, Jing Wang, You Zhang

Faculty, Staff and Student Publications

Objective. Deformable liver motion tracking using a single x-ray projection enables real-time motion monitoring and treatment intervention. We introduce a conditional point cloud diffusion (PCD) model-based framework for accurate and robust liver motion tracking from arbitrarily angled single x-ray projections. Approach. We propose a conditional PCD model for liver motion tracking (PCD-Liver), which estimates volumetric liver motion by solving deformable vector fields (DVFs) of a prior liver surface point cloud, based on a single x-ray image. It is a patient-specific model of two main components: a rigid alignment model to estimate the liver’s overall shifts, and a conditional PCD …

Granite Staters Wary Of One Big Beautiful Bill But Support No Taxes On Tips & Overtime 6/25/2025, Unh Survey Center

All UNH Survey Center Polls

A majority of New Hampshire residents do not want the U.S. Congress to pass President Trump's signature piece of legislation, the "One Big Beautiful Bill Act," amid bipartisan concern about the federal debt. Despite opposition to the overall bill, Granite Staters favor the provision of the bill to eliminate taxes on tips and overtime and are divided on work requirements for Medicaid and making the 2017 tax cuts permanent. Elon Musk is a largely unpopular figure in New Hampshire and nearly half of state residents believe the Department of Government Efficiency has had a negative effect on the country. Approval …

Mainers Disapprove Of One Big Beautiful Bill, Increasingly Disapprove Of Trump Handling Of Economy 6/25/2025, Unh Survey Center

All UNH Survey Center Polls

Less than one-third of Maine residents want Congress to pass the "One Big Beautiful Bill Act," President Trump's major piece of legislation. However, a majority favor the provision of the bill which would eliminate taxes on tips and overtime. Elon Musk is an unpopular figure in Maine following his departure from the federal government and more than half of state residents believe the Department of Government Efficiency has had a negative effect on the country. Approval of Trump's handling of the economy among Mainers has declined since April and bipartisan majorities express concern about the federal debt.

Two-Thirds Of Vermonters Reject One Big Beautiful Bill Amid Bipartisan Concern About Budget Deficit 6/25/2025, Unh Survey Center

All UNH Survey Center Polls

Most Vermont residents do not want Congress to pass President Trump's "One Big Beautiful Bill Act." Majorities oppose notable provisions of the Act such as making the 2017 tax cuts permanent and removing tax credits for electric vehicles and solar energy. Following his departure from the federal government, Elon Musk is an unpopular figure in Vermont and two-thirds of state residents believe the Department of Government Efficiency (DOGE) has had a negative effect on the country. Vermonters continue to disapprove of Trump's handling of the economy, immigration, and his overall job performance.

Integrated Proteomic And Targeted Next Generation Sequencing Reveal Relevant Heterogeneity In Lower-Grade Meningioma And Anxa3 As A New Target In Nf2 Mutated Meningiomas, Maryam Shah, Yeasmin Akther, Claire Adams, Matt Banton, Vikram Sharma, Emanuela Ercolano, David A Hilton, Kathreena M. Kurian, Liyam Laraba, Waldemar Woznica, David Parkinson, Leandro Jose De Assis, Oliver Hanemann

Peninsula Medical School

Background: Meningiomas, the most common primary brain tumours, are classified by the World Health Organization (WHO) into grades 1, 2, and 3. Some grade 1 tumours exhibit increased clinical aggressiveness, with the biallelic mutation of NF2 being the most frequently reported. Methods: In our study, we analysed the most common driver mutations (NF2, AKT1, KLF4, and TRAF7) in meningioma by genomics describing co-occurrences and new mutations. Furthermore, tumour tissue bearing the driver mutations was analysed by proteomics. The relevance of the specific target found in the most common driver mutation in meningiomas (NF2) was validated in vitro using both lower …

Cannabis Use In Women And Sexual Dysfunction, Becky K. Lynn, Julia D. López, Morgan E. Link, E C. Campian

2020-Current year OA Pubs

No abstract provided.

What Drives Clinic Follow-Up After Traumatic Spinal Injury? An Observational Cohort Study From Tanzania, Chibuikem A Ikwuegbuenyi, Julie Woodfield, Romani Roman Sabas, Sean Inzerillo, Noah Willett, Magalie Cadieux, Scott L Zuckerman, Francois Waterkeyn, Halinder S Mangat, Hamisi K Shabani, Roger Härtl

2020-Current year OA Pubs

OBJECTIVES: To evaluate factors associated with clinic follow-up after traumatic spinal injury (TSI) in Tanzania, focusing on demographic, injury-related and hospital variables. We hypothesised that socioeconomic and injury-specific factors would predict follow-up adherence.

DESIGN: Retrospective observational cohort study.

SETTING: Tertiary government referral centre for neurosurgery and orthopaedics in Dar es Salaam, Tanzania.

PARTICIPANTS: 443 adults with TSI admitted between September 2016 and October 2021. Inclusion criteria included survival to discharge and availability of the discharge date. Patients with missing data were excluded.

PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcomes were any clinic follow-up and 1-year follow-up post-discharge. Secondary outcome was …

Sosiologi Hukum Dan Perubahan Sosial: Studi Kasus Uu No. 35 Tahun 2014 Tentang Perlindungan Anak Sebagai Respon Terhadap Kesadaran Sosial Yang Meningkat Akan Hak Anak, Fahrul Rozi

Jurnal Hukum & Pembangunan

Dalam konteks sosial yang dinamis, kesadaran akan hak anak telah meningkat, terlihat dari perhatian masyarakat terhadap isu-isu seperti kekerasan, eksploitasi, dan diskriminasi. Meskipun UU No. 35 Tahun 2014 memberikan kerangka hukum yang kuat untuk melindungi hak-hak anak, tantangan dalam pelaksanaannya masih ada, termasuk kurangnya sumber daya dan koordinasi antar lembaga. Anak jalanan, sebagai kelompok yang paling rentan, sering kali terjebak dalam siklus kemiskinan dan stigma sosial, yang menghambat upaya perlindungan. Menekankan pentingnya edukasi dan sosialisasi mengenai hak anak, serta peran aktif masyarakat dan media dalam mendukung perlindungan anak. Dengan kolaborasi antara pemerintah, masyarakat, dan lembaga swadaya masyarakat, diharapkan hak-hak anak …

Exploring The Translation Lookaside Buffer (Tlb) For Low-Level Task Differentiation And Classification, Cristian Agredo, Daniel F. Koranek, Christine M. Schubert, Jose A. Gutierrez Del Arroyo, Tor J. Langehaug, Scott R. Graham

Faculty Publications

The primary focus of modern Central Processing Unit (CPU) technologies is performance improvement, with security often considered a secondary concern. As a result, vulnerabilities within the system are overlooked. While significant research, both offensive and defensive, has been conducted on CPU caches, relatively little attention has been given to the Translation Lookaside Buffer (TLB) due to its perceived lack of data granularity. Prior studies have typically combined multiple Hardware Performance Counters (HPCs) or relied on timing analysis to extract meaningful insights. In contrast, this study introduces a novel methodology that leverages only TLB related HPCs for multi-task classification, without incorporating …

Pengaruh Asset Life Cycle Management Terhadap Performa Aset Negara, Budi Susanto, Muhammad Halley Yudhistira

Jurnal Kebijakan Ekonomi

This study examines the impact of government intervention in asset management systems on the performance of state-owned assets. Using Asset Life Cycle Management (ALCM) indicators and binary logistic regression, the findings reveal that three key aspects of ALCM—strategy and planning, acquisition, and operation and maintenance—significantly influence asset performance. The impact of ALCM policies varies by asset location, categorized into five major regions: Sumatra, Java, Kalimantan, Bali-Nusa Tenggara, and Papua. These results provide empirical evidence that effective asset management policies positively contribute to optimizing the performance of state assets.

Carbon Capture Storage Sand Control Injection Sleeve, Baker Hughes Company

Defensive Publications Series

This solution is to address carbon capture storage wells that are required to have re-close/re-open sand control injection sleeve across wells' injection lifecycle. This Sand Control Injection Sleeve’s novelty comes from the design features addressing excessive injection rate while ensuring re-close/re-open feature, the design features also address sand screen erosion prevention.

Xplain: Xai For Interpretable Llms Through Perturbation Analysis And Normalized Vector Similarity, Gopala Dhar, Sharmila Devi

Defensive Publications Series

This document introduces XAI methodology, referred to as XPLAIN, to address the challenges of LLM interpretability by developing a perturbation-based normalized vector similarity metric to identify and quantify word level importance of the prompt provided to an LLM on its generated output. By analyzing which words or phrases most significantly influence an LLM's decisions, the described techniques enhance the explainability and interpretability of large language models. The approach perturbs the prompt via masking words to generate several outputs through the LLM and then compares the outputs with the generated output of the unperturbed prompt through vector-based similarity at a semantic …

Enabling Privacy-Compliant And Context-Aware Tool Use By Artificial Intelligence Agents, Victor Carbune, Nevan Wichers, Oriana Riva

Defensive Publications Series

This disclosure describes techniques that enable an AI agent to learn the appropriate mode of access to user data. In a first mode, the agent can obtain user-related data by directly asking the user and obtaining explicit permission from the user. In a second mode, the AI agent determines situations where it is appropriate to obtain, with user permission and based on user interactions and settings, user data via authenticated apps. The techniques enable the agent to discern when to access a certain personalization tool based on inferring what the user may find appropriate. The techniques enable an AI agent …

Automatic Documentation Updates Using Artificial Intelligence, Matija Blagus, Ricardo Gutierrez, Jorge Rúa, Santosh Guddala

Defensive Publications Series

Many organizations rely on a combination of first-party and third-party software to support their business units in solving specific challenges. These software components are often interconnected, resulting in a complex mesh of systems that underpin critical business processes. This disclosure describes techniques that use infrastructure-as-code (IaC) principles to leverage information available within a codebase or systems to automatically generate system descriptions and documentation using artificial intelligence (AI). The techniques consolidate data from multiple sources to synchronize documentation across entire systems, eliminating the need for manual updates and mitigating ambiguity regarding system states.

Self-Adaptive Curvature Screen For Dynamic User Position, Hp Inc

Defensive Publications Series

Maintaining the same visual distance and making the picture more realistic as it appears in the real world is an important factor that deepens immersion. Generally, the edge of the screen of a flat display often causes deformation and distortion due to the viewing angle.

The purpose of the curved display is trying to maintain the same viewing distance when viewing images from different angles, which not only reduces the distortion of the edge of the screen. It also improves visual comfort and allows people to enter an immersive state through virtual scenes.

In this disclosure, the proposed is an …

Split Firing Algorithm For Movable Printers, Hp Inc

Defensive Publications Series

The movable printers are now reference robots in construction world that draws lines and text on the floor, translating architects' and engineers' digital plans into real floorplans. This accelerates construction and speeds up their work. Due to cost and simplicity, the movable printers do not include most of the hardware found in standard printers that ensure printhead reliability, extended autonomy, and unlimited power when connected to the electricity network.

As a result, the weight, size, and equipment must be minimized. One of the biggest challenges to take in account is the power supply. During movement and extensive printhead usage, combined …

Powerful Usb-C, Hp Inc

Defensive Publications Series

This concept is a new USB-C connector to deliver higher power and Extra bandwidth with simplified, single-cable installation.

Ai Assisted Pen Drop Detection, Hp Inc

Defensive Publications Series

Active pens have been a tool to enhance productivity in office environments and in school class. This publication proposed a method to enable active pen drop detection by utilizing IMU/Gyro sensor with AI assisted algorithm to detect active pen dropping events and implement buzzer, haptic module, or Bluetooth communication to host computer system to alert end users that their active pen is lost. This function can prevent end users losing their active pens causing productivity loss in the office or in the school.

The Gift Shop - Celebrates (A Journey Just Begun)

University anniversary celebration materials

No abstract provided.

Sustainable Tourism Behaviour Through Walking Tour: A Qualitative Study To Walking Tour Participants In Jakarta, Melisa Bunga Altamira, Khairunnisa Devani Aqtus Permana Putri

Journal of Indonesian Tourism and Policy Studies

As urban tourism continues to rise, walking tours have emerged as a low-impact, environmentally friendly, and culturally immersive form of tourism. This study explores the relationship between walking tours and the development of sustainable tourism behaviour among participants in Jakarta, Indonesia. Using a qualitative research approach, this study elaborates the motivations, perceptions, and behavioural changes of individuals who have participated in walking tours across Jakarta’s historical and cultural sites. Data were collected through in-depth interviews and participant observations, focusing on themes such as environmental awareness, appreciation of local culture, and reduced dependency on motorized transport. The findings suggest that walking …

International Material Handling Research Colloquium Program, International Material Handling Research Colloquium Program

International Material Handling Research Colloquium

No abstract provided.

Director, Military Cyber Institute, Joseph Schafer

Military Cyber Affairs

No abstract provided.

Throughput Of Ascon Compared With Popular Iot Encryption Algorithms, Mitchel R. Harvey (Ryan), Andrew M. Kaiser, Garrett W. Hoiness

Military Cyber Affairs

No abstract provided.

Anomaly Detection Of Network Layer Attacks Against Cyber Physical Systems Using Machine Learning And Deep Learning Techniques, James Alger, Michael Tu

Military Cyber Affairs

This research paper presents the analysis of using machine learning and deep learning algorithms on detecting anomalous network traffic in Cyber-Physical Systems (CPS). Using a real PLC CPS-based system, normal and anomalous network traffic will be captured using Wireshark. The research analyzes a DDoS attack. The focus of the research is to identify the most effective feature combinations and evaluate them on ML and DL models. The emphasis is on enhancing detection strategies rather than exploiting device vulnerabilities. The detection of network attacks often involves handling a vast array of high-level features. Previous studies (Li & Chasaki, 2022) apply machine …

Characterizing Caldera’S Cyber Attack Emulation Capabilities, Caleb Chang, Matthew Cao, Kenyou Teoh, Ekzhin Ear, Shouhuai Xu

Military Cyber Affairs

Autonomous cyber attack emulation can aid cyber defenders to identify and remediate cyber risks. MITRE’s Caldera software is the state-of-the-practice for automated attack emulation. Yet, it has not been systematically analyzed, putting its performance and effectiveness into question. This paper systematically characterizes Caldera’s architecture, abilities and use cases, and assesses its strengths and weaknesses. It draws useful insights, such as: Caldera excels in stealthy access and execution tactics to pilfer data against Windows operating systems. It also discusses two directions for Caldera improvement: module-level automation and end-to-end attack emulation.

The Digital Battlefield: Safeguarding Military Drones Against Cyberattacks, Jason Ashong, Arun Venkitanarayanan, Benjamin Yankson

Military Cyber Affairs

The Internet of Battlefield Things (IoBT) is an advanced network of interconnected devices that significantly enhance military operations through real-time data exchange and situational awareness. While IoBT offers tactical advantages like improved surveillance, reconnaissance, and operational effectiveness, it also introduces substantial cybersecurity risks. Adversaries can exploit vulnerabilities within these networks, potentially compromising mission integrity and national security. This research examines the cybersecurity measures of commercial drone controllers and their correlation with military devices. It aims to enhance future vulnerability assessments with advanced tools and approaches to better secure critical military operations. The study highlights the need for robust security architectures …

Using Blockchain Technology To Help Secure America's Defense Critical Infrastructure, Vimal Buck, Aerin Krebs, Brynn Hillard, Jakob Gerha, Joseph Lutma, Srikar Maduposu, Ted Allen

Military Cyber Affairs

Critical water infrastructure in the United States faces increasing cybersecurity threats from state-sponsored actors, with potentially devastating consequences for national security, economic stability, and public health. (Cybersecurity and Infrastructure Security Agency, 2025). This infrastructure supports defense critical assets and is actively being targeted by various state-sponsored hacking groups, which poses a major concern for civilians and military alike. K. Herath (personal communication, February 24, 2025) reported being aware of two attacks on Ohio water systems during his tenure as Cybersecurity Strategic Advisor to Ohio Governor Mike DeWine.

Water is essential to everyday life and defense and presents as a high-value …

Network And Multipath Traceroute Visualization, Cameron Makowski

Military Cyber Affairs

TraceCam introduces a new paradigm in network path analysis, leveraging GPU-accelerated WebGL visualization, advanced traceroute integrations, and AI-driven insights to transform complex routing data into actionable intelligence. Early prototypes have demonstrated significant improvements in performance, clarity, and multi-path discovery, overcoming traditional limitations in traceroute analysis. By incorporating retrieval-augmented language models and enriched metadata sources like IPinfo.io, TraceCam enables automated anomaly detection, contextual explanations, and rapid root-cause analysis, enhancing operational efficiency. The platform’s architecture ensures scalability and adaptability, supporting deeper investigations and real-time situational awareness. Future development will focus on clustering-based anomaly detection, expanded geographic visualizations, and enhanced AI-generated analysis to …