Related papers: The Fermilab Test Beam Facility Data Acquisition S…
The Ultra-Fast Flash Observatory (UFFO) Pathfinder is a payload on the Russian Lomonosov satellite, scheduled to be launched in November 2011. The Observatory is designed to detect early UV/Optical photons from Gamma-Ray Bursts (GRBs).…
The Kaos spectrometer is maintained by the A1 collaboration at the Mainz Microtron MAMI with a focus on the study of (e,e'K^+) coincidence reactions. For its electron-arm two vertical planes of fiber arrays, each comprising approximately 10…
Log anomaly detection (LAD) is essential to ensure safe and stable operation of software systems. Although current LAD methods exhibit significant potential in addressing challenges posed by unstable log events and temporal sequence…
This paper describes a comprehensive prototype of large-scale fault adaptive embedded software developed for the proposed Fermilab BTeV high energy physics experiment. Lightweight self-optimizing agents embedded within Level 1 of the…
We have developed a computer program interfaced with the ACNET environment of Fermilab accelerators to measure energy spread of the proton beam from the LINAC at an injection into the Booster. It uses a digitizing oscilloscope and provides…
Noisy Intermediate-Scale Quantum (NISQ) devices, while accessible via cloud platforms, face challenges due to limited availability and suboptimal quality. These challenges raise the risk of cloud providers offering fraudulent services. This…
Deploying ultra-dense networks that operate on millimeter wave (mmWave) band is a promising way to address the tremendous growth on mobile data traffic. However, one key challenge of ultra-dense mmWave network (UDmmN) is beam management due…
Distributed acoustic sensing (DAS) systems generate continuous, ultra-high-channel-count data streams at rates that exceed the capabilities of conventional batch-oriented analysis frameworks. As a result, essential tasks such as interactive…
Muon scattering tomography is a non-destructive imaging technique that utilizes the penetrating properties and multiple Coulomb scattering of muons to produce detailed internal images of objects. This information is crucial for various…
Filter bank-based multicarrier (FBMC) systems are currently being considered as a prevalent candidate for replacing the long established cyclic prefix (CP)-based orthogonal frequency division multiplexing (CP-OFDM) in the physical layer of…
In recent years, with the increasing popularity of "Smart Technology", the number of Internet of Things (IoT) devices and systems have surged significantly. Various IoT services and functionalities are based on the analytics of IoT…
In high energy physics experiments (HEP), high speed and fault resilient data communication is needed between detectors/sensors and the host PC. Transient faults can occur in the communication hardware due to various external effects like…
Most traditional false data injection attack (FDIA) detection approaches rely on a key assumption, i.e., the power system can be accurately modeled. However, the transmission line parameters are dynamic and cannot be accurately known during…
We outline the design of beam experiments for the electron linac at the Fermilab Accelerator Science and Technology (FAST) facility and for the Integrable Optics Test Accelerator (IOTA), based on synchrotron light emitted by the electrons…
Data-driven methods have demonstrated strong predictive capabilities in fluid mechanics, yet most current applications still focus on simplified configurations, often characterised by statistical stationarity or limited temporal…
Since the traffic conditions change over time, machine learning models that predict traffic flows must be updated continuously and efficiently in smart public transportation. Federated learning (FL) is a distributed machine learning scheme…
The closed-off structure of the Fermilab Drift Tube Linac precludes a robust array of instrumentation from directly monitoring the H- beam that is accelerated from 750 keV to 116 MeV. To improve beam tuning and operational assessment of…
Recent reviews find that the vast majority of published healthcare federated learning (FL) studies never reach real-world deployment. We developed an embedding-based FL pipeline for iron deficiency prediction from routine full blood count…
In this work, we demonstrate the deployment of a hardware-accelerated machine learning (ML) inference system integrated into a real-time processing at the DIII-D tokamak fusion reactor. The team has successfully deployed an AMD/Xilinx…
The paper proposes an on-line monitoring framework for continuous real-time safety/security in learning-based control systems (specifically application to a unmanned ground vehicle). We monitor validity of mappings from sensor inputs to…