Related papers: A Modular Object Oriented Data Acquisition System …
Object-centric process mining is emerging as a promising paradigm across diverse industries, drawing substantial academic attention. To support its data requirements, existing object-centric data formats primarily facilitate the exchange of…
Structural vibration testing plays a key role in aerospace engineering for evaluating dynamic behaviour, ensuring reliability and verifying structural integrity. These tests rely on accurate and robust data acquisition systems (DAQ) to…
CuboDAQ is a custom data acquisition system to read out SiPM-based detectors. It features electronic boards to digitize the SiPMs signal, an FPGA-based system-on-module board, the connectivity to transmit the data to a central server, and…
Domain adaptation for object detection (DAOD) has recently drawn much attention owing to its capability of detecting target objects without any annotations. To tackle the problem, previous works focus on aligning features extracted from…
A data acquisition (DAQ) system is described which will be used for the next generation of prototype calorimeters using particle flow algorithms for the International Linear Collider (ILC). The design is sufficiently generic and scalable…
Gravitational-wave data analysis relies on accurate and efficient methods to extract physical information from noisy detector signals, yet the increasing rate and complexity of observations represent a growing challenge. Deep learning…
Modern production data processing and machine learning pipelines on the cloud are critical components for many cloud-based companies. These pipelines are typically composed of complex workflows represented by directed acyclic graphs (DAGs).…
Meta-software for data acquisition (DAQ) is a new approach to design the DAQ systems for experimental setups in experiments in high energy physics (HEP). It abstracts from experiment-specific data processing logic, but reflects it through…
Region proposal is critical for object detection while it usually poses a bottleneck in improving the computation efficiency on traditional control-flow architectures. We have observed region proposal tasks are potentially suitable for…
The first simultaneous operation of the AURIGA detector and the LIGO observatory was an opportunity to explore real data, joint analysis methods between two very different types of gravitational wave detectors: resonant bars and…
Modern DAQ systems typically use the FPGA-based PCIe cards to concentrate and deliver the data to a computer used as an entry node of the data processing network. This paper presents a QEMU-based methodology for the co-development of the…
Advanced LIGO and Advanced Virgo ground-based interferometers are instruments capable to detect gravitational wave signals exploiting advanced laser interferometry techniques. The underlying data analysis task consists in identifying…
Unmanned aerial vehicles (UAVs) can be critical for time-sensitive data collection missions, yet existing research often relies on simulations that fail to capture real-world complexities. Many studies assume ideal wireless conditions or…
As autonomous agentic AI systems see increasing adoption across organisations, persistent challenges in alignment, governance, and risk management threaten to impede deployment at scale. We present AURA (Agent aUtonomy Risk Assessment), a…
Marine in-situ data is collected by sensors mounted on fixed or mobile systems deployed into the ocean. This type of data is crucial both for the ocean industries and public authorities, e.g., for monitoring and forecasting the state of…
Fast, incremental evolution of physics instrumentation raises the question of efficient software abstraction and transferability of algorithms across similar technologies. This contribution aims to provide an answer by introducing Track…
Multimodal Large Language Models (MLLMs) have significantly advanced GUI agents, yet long-horizon automation remains constrained by two critical bottlenecks: context overload from raw sequential trajectory dependence and architectural…
During 2015 and 2016, the Laser Interferometer Gravitational-Wave Observatory (LIGO) conducted a three-month observing campaign. These observations delivered the first direct detection of gravitational waves from binary black hole mergers.…
This paper presents ORXE, a modular and adaptable framework for achieving real-time configurable efficiency in AI models. By leveraging a collection of pre-trained experts with diverse computational costs and performance levels, ORXE…
We introduce Diffusion Active Learning, a novel approach that combines generative diffusion modeling with data-driven sequential experimental design to adaptively acquire data for inverse problems. Although broadly applicable, we focus on…