TS-074364 — Senior executives struggle to understand and prioritize cybersecurity risk in business terms. Existing vulnerability scoring systems rely on opaque or arbitrary measures that fail to connect cybersecurity decisions to financial impact, staffing costs, or operational tradeoffs. As a result, organiz…

TS-074268 — Real-time and free-breathing MRI applications, particularly in cardiovascular imaging, require high temporal resolution to capture rapid physiological dynamics. However, optimal temporal resolution is often patient- and application-specific and may not be known before the scan. Existing Cartesian …

TS-074095 — Hybrid and electrified vehicles face increasing pressure to simultaneously reduce fuel consumption and tailpipe emissions, particularly during transient operating conditions such as cold start. Conventional rule-based or static control strategies struggle to optimally manage the tradeoffs among en…

TS-073841 — Current federated learning (FL) systems face significant challenges in efficiently aggregating model updates over wireless networks, especially in environments with diverse data and varying channel conditions. There is a critical need for a solution that enhances bandwidth efficiency, personalizat…

TS-073818 — Autonomous and advanced driver-assistance systems require extensive testing across rare, hazardous, and edge-case scenarios to ensure safety and regulatory readiness. Existing approaches (pure simulation, hardware-in-the-loop, proving grounds, or public-road testing) each suffer from tradeoffs in …

TS-073768 — Electrified and hybrid vehicle powertrains are increasingly complex, integrating mechanical, electrical, thermal, and emissions subsystems with both continuous and discrete decision variables. Existing energy management and co‑optimization approaches typically rely on simplified models, sequenti…

TS-073717 — Spiking Neural Networks (SNNs) promise ultra-low-power, low-latency AI for edge and neuromorphic computing, but their adoption is constrained by fundamental training challenges. SNN performance is highly sensitive to how training data are collected (e.g., lighting, sensor settings, noise), leading…

TS-073692 — Fleet operators face increasing pressure to reduce operating costs and emissions while maintaining performance and reliability. Choosing the “right” truck (diesel, alternative fuel, or battery electric) for a specific duty cycle remains largely heuristic, conservative, and error‑prone. As a …

TS-073587 — Magnetic nanoparticles are widely used in applications such as magnetic hyperthermia, catalysis, sensing, and data storage, yet their performance is often limited by poor control over key magnetic properties. Existing materials typically rely on size or shape control alone, which provides limited …

TS-073553 — Positioning, navigation, and timing (PNT) systems increasingly seek alternatives or complements to GNSS due to vulnerability to interference, jamming, and limited performance in challenged environments. While low Earth orbit (LEO) communication satellites offer strong signals and favorable geometr…

TS-073358 — Reliable positioning, navigation, and timing (PNT) in GNSS‑denied or disrupted environments remains a critical challenge for defense, transportation, and autonomous systems. While low Earth orbit (LEO) communications satellites offer powerful signals and rapid geometry changes, they are typicall…

TS-073339 — Positioning, navigation, and timing (PNT) resilience is increasingly critical as GNSS vulnerabilities become more apparent in contested, denied, or degraded environments. Low Earth orbit (LEO) communication satellites offer a promising alternative PNT source, but their utility is limited by poorly…

TS-073254 — Industries operating safety‑critical and asset‑intensive systems struggle to leverage the full value of disparate maintenance data sources. Current maintenance management and optimization tools operate in silos, limiting real‑time decision‑making, automation, and scalability. No existing s…

TS-073225 — In today's world, we are increasingly using low-cost devices with limited resources (often referred to as "edge devices") which are supported by connected high-performance servers. However, these edge devices often can't handle complex tasks such as classifying data. To make this possible, we need…

TS-073173 — Modern navigation systems increasingly rely on signals of opportunity such as 5G and LEO satellite downlinks, but these signals often lack public reference‑signal specifications, may be dynamic or on‑demand, and can suffer from severe Doppler effects. Conventional receivers cannot reliably acq…

TS-073146 — As industrial systems become increasingly digital and interconnected, traditional risk assessment tools struggle to capture how cyber threats interact with physical processes in real time. Existing methods typically assess hardware failures or isolated cyber events, but they cannot model how attac…

TS-073138 — Designing online monitoring (OLM) for safety‑critical systems is constrained by scarce early‑stage operational data and by quantitative models that are slow to build, brittle across configurations, and costly to iterate. This creates expensive sensor networks with blind spots, poor diagnosabil…

TS-073111 — Urban intersections are among the highest‑risk environments for automated and human‑driven vehicles due to occlusions, complex right‑of‑way, mixed traffic, and inconsistent connectivity. On‑board perception alone often misses beyond‑line‑of‑sight actors, while centralized or game�…

TS-073103 — Physical protection remains a major driver of nuclear plant operations and maintenance costs, yet current security risk models rely on conservative assumptions and sparse empirical data on how defenders and operators actually behave under extreme threat. They rarely capture errors of commission, k…

TS-073031 — Operators of large, complex facilities struggle to balance revenue, maintenance, and regulatory safety constraints under uncertainty. Existing tools typically optimize only a subset of factors without a unified, real‑time view of component health and future degradation. Advanced reactors and oth…