Related papers: Enriching the physics program of the CMS experimen…

We present a flexible and scalable approach to address the challenges of charged particle track reconstruction in real-time event filters (Level-1 triggers) in collider physics experiments. The method described here is based on a full-mesh…

Connected vehicles (CVs) can capture and transmit detailed data such as vehicle position and speed through vehicle-to-vehicle and vehicle-to-infrastructure communications. The wealth of CV data provides new opportunities to improve safety…

The growing demand for efficient cloud storage solutions has led to the widespread adoption of Solid-State Drives (SSDs) for caching in cloud block storage systems. The management of data writes to SSD caches plays a crucial role in…

Cyber-physical systems (CPS) encounter a large volume of data which is added to the system gradually in real time and not altogether in advance. As the volume of data increases, the domain of the control strategies also increases, and thus…

We introduce a modified model of random walk, and then develop two novel clustering algorithms based on it. In the algorithms, each data point in a dataset is considered as a particle which can move at random in space according to the…

With the increasing capabilities of machine learning systems and their potential use in safety-critical systems, ensuring high-quality data is becoming increasingly important. In this paper we present a novel approach for the assurance of…

Kernel methods augmented with random features give scalable algorithms for learning from big data. But it has been computationally hard to sample random features according to a probability distribution that is optimized for the data, so as…

Many scientific applications opt for particles instead of meshes as their basic primitives to model complex systems composed of billions of discrete entities. Such applications span a diverse array of scientific domains, including molecular…

We develop a machine learning method for mapping data originating from both Standard Model processes and various theories beyond the Standard Model into a unified representation (latent) space while conserving information about the…

In recent years, there has been a growing demand for improved autonomy for in-orbit operations such as rendezvous, docking, and proximity maneuvers, leading to increased interest in employing Deep Learning-based Spacecraft Pose Estimation…

Studies of heavy-ion collisions at the LHC will benefit from an array of qualitatively new probes not readily available at lower collision energies. These include fully formed jets at ET > 50 GeV, Z0's and abundantly produced heavy flavors.…

First searches for new physics phenomena using the LHC 7 TeV proton-proton collision data collected by the CMS detector in 2010 are reviewed. Results are presented of searches for new physics in events with hadronic jet pairs, and for heavy…

We introduce a temporal scheme for data sampling, based on a variable delay between two successive data acquisitions. The scheme is designed so as to reduce the average data flow rate, while still retaining the information on the data…

Data augmentation improves the convergence of iterative algorithms, such as the EM algorithm and Gibbs sampler by introducing carefully designed latent variables. In this article, we first propose a data augmentation scheme for the…

Machine learning (ML) is a rapidly growing area of research in the field of particle physics, with a vast array of applications at the CERN LHC. ML has changed the way particle physicists conduct searches and measurements as a versatile…

Feature extraction is crucial for human activity recognition (HAR) using body-worn movement sensors. Recently, learned representations have been used successfully, offering promising alternatives to manually engineered features. Our work…

The prospects of the ATLAS and CMS experiments at LHC for beyond standard model searches are depicted in this document. The presented studies concentrate on the search plans for supersymmetry (SUSY) and beyond in the first few years of data…

Thermal-Hydraulic (TH) experiments provide valuable insight into the physics of heat and mass transfer and qualified data for code development, calibration and validation. However, measurements are typically collected from sparsely…

Parking challenges escalate significantly during large events such as concerts and sports games, yet few studies address dynamic parking lot assignments in these occasions. This paper introduces a smart navigation system designed to…

The search for new physics is a major goal of the LHC physics program. As excitement grows for the upcoming start of Run 2, I review the CMS and ATLAS searches for physics beyond the Standard Model from Run 1 and present recent analyses.…