Efficient Data Management System
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AeroMesa: Efficient Data Management System for Multi-Dimensional Spatio-Temporal Trajectories
arXiv:2606.09581v1 Announce Type: new Abstract: The rapid growth of trajectory data -- especially the dense 4D traces generated by unmanned aerial vehicles (UAVs) -- is placing mounting pressure on spatio-temporal data management systems. Existing HBase-based trajectory indexes suffer from three limitations: coarse-grained temporal pruning, locality-unfriendly XZ2 spatial encodings with workload-blind ordering, and severe row-key interval fragmentation when altitude is jointly encoded with...
Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models
Announce Type: new Abstract: Data-driven Prognostics and Health Management (PHM) uses time-varying condition-monitoring data to diagnose system states and estimate remaining useful life in engineered assets. These tasks are central to maintenance planning, but industrial PHM data are often fragmented, partially observed, and poorly labeled, which hinders supervised learning. Foundation models offer a route toward reusable predictive systems, yet most time-series foundation models are...
From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction
Announce Type: new Abstract: Efficient acquisition, storage, and utilization of traffic data are critical challenges in spatio-temporal data management. Most traffic data systems collect and store observations at fixed, coarse-grained temporal intervals to reduce storage and computation costs. However, such coarse-grained data severely limits downstream applications that require predictions at a finer temporal granularity.
LLM-Enhanced Dialogue Management for Full-Duplex Spoken Dialogue Systems
Announce Type: replace Abstract: Achieving full-duplex communication in spoken dialogue systems (SDS) requires real-time coordination between listening, speaking, and thinking. This paper proposes a semantic voice activity detection (VAD) module as a dialogue manager (DM) to efficiently manage turn-taking in full-duplex SDS. Implemented as a lightweight (0.5B) LLM fine-tuned on full-duplex conversation data, the semantic VAD predicts four control tokens to regulate turn-switching and...
Fides: Secure and Scalable Asynchronous DAG Consensus via Trusted Components
Announce Type: replace Abstract: DAG-based BFT consensus has attracted growing interest in distributed data management systems for consistent replication in untrusted settings due to its high throughput and resilience to asynchrony. However, existing protocols still suffer from high communication overhead and long commit latency. In parallel, introducing minimal hardware trust has proven effective in reducing the complexity of BFT consensus.
Fides: Secure and Scalable Asynchronous DAG Consensus via Trusted Components
arXiv:2501.01062v3 Announce Type: replace Abstract: DAG-based BFT consensus has attracted growing interest in distributed data management systems for consistent replication in untrusted settings due to its high throughput and resilience to asynchrony. However, existing protocols still suffer from high communication overhead and long commit latency. In parallel, introducing minimal hardware trust has proven effective in reducing the complexity of BFT consensus.
Efficient Multi-Agent Optimization of Optical Power in S+C+L-Band Systems
Electrical Engineering and Systems Science > Systems and Control [Submitted on 4 Jun 2026] Title:Efficient Multi-Agent Optimization of Optical Power in S+C+L-Band Systems View PDF HTML (experimental)Abstract:We propose an AI Agent tailored for link power management in multi-band systems. In S+C+L band span-level study, the agent efficiently solves various optimization objectives.
RESCAST-100K: A Comprehensive Dataset for Cross-Domain Residential Load and Indoor Temperature Forecasting
arXiv:2606.02852v1 Announce Type: new Abstract: Accurate short-term forecasting of residential energy load and indoor temperature is essential for home energy management systems, grid-level demand response, and community energy efficiency efforts. Domain adaptation and transfer learning have shown promise for improving forecasting accuracy under data heterogeneity and scarcity commonly seen in residential settings. However, progress is limited by the lack of comprehensive residential...
Smart pipelines: Can AI protect the world’s energy lifelines?
As ageing pipelines face growing risks, the energy industry is increasingly turning to AI and smart monitoring systems to improve their safety and efficiency. Around 500,000 kilometres of oil and gas pipelines worldwide need to be renovated, rebuilt or upgraded, while leaks, ruptures and incidents already cost the sector more than $7 billion (€6bn) a year — and roughly 40% of failures go undetected in the first 24 hours, according to industry experts speaking at the Baku Energy Forum. The...
ZTE showcases AI-driven project management innovations at the 14th IPMA Research Conference 2026
ZTE Corporation today showcased its pioneering achievements in digital transformation and AI-driven project management at the 14th IPMA Research Conference in Bogotá, Colombia. During the conference, Wang Yuzhu, Managing Director of Engineering Services at ZTE Colombia, and Jose Perez, Senior Expert in Engineering Delivery Management at ZTE, delivered a keynote speech themed "The Digital and Intelligent Future of Project Management", highlighting ZTE's practical experiences and innovative...