Related papers: LEP Data@EDM4hep: mitigating data loss risks by in…

Homomorphic encryption (HE) allows secure computation on encrypted data without revealing the original data, providing significant benefits for privacy-sensitive applications. Many cloud computing applications (e.g., DNA read mapping,…

Mobile edge computing (MEC) is an emerging communication scheme that aims at reducing latency. In this paper, we investigate a green MEC system under the existence of an eavesdropper. We use computation efficiency, which is defined as the…

The cross section of the process e+e- -> Ze+e is measured with 0.7fb^-1 of data collected with the L3 detector at LEP. Decays of the Z boson into quarks and muons are considered at centre-of-mass energies ranging from 183GeV up to 209GeV.…

Fine-tuning plays a crucial role in enabling pre-trained LLMs to evolve from general language comprehension to task-specific expertise. To preserve user data privacy, federated fine-tuning is often employed and has emerged as the de facto…

These proceedings summarize the latest measurements on top production, top properties and searches using the ATLAS detector at the LHC. The measurements are performed on $pp$ collision data with a center of mass energy $\sqrt{s} = 7, 8$ and…

We present results from SMEFiT3.0, a global SMEFT fit of Higgs, top quark, and diboson production data from the LHC. Our updated analysis includes recent inclusive and differential measurements from the LHC Run II, together with the exact…

Federated learning (FL) is able to manage edge devices to cooperatively train a model while maintaining the training data local and private. One common assumption in FL is that all edge devices share the same machine learning model in…

Studies are presented of the selection of events consistent with top quark pair production in data recorded by the CMS detector at the LHC, corresponding to an integrated luminosity of 0.84+/-0.09 1/pb and at center-of-mass energy sqrt{s}=7…

The period 1989-2000 provided a huge yield of precise electroweak data from the LEP and SLC experiments. Many analyses of these data are now complete, but others, particularly of the full LEP-2 data samples, continue. The main electroweak…

Since no Standard Model Higgs boson was discovered at LEP the searches were extended to beyond the Standard Model Higgs scenarios. A selection of final results from searches carried out by the four LEP experiments ALEPH, DELPHI, L3 and OPAL…

This note presents a combination of published and preliminary electroweak results from the four LEP collaborations ALEPH, DELPHI, L3 and OPAL based on electron-positron collision data taken at centre-of-mass energies above the Z-pole, $130…

The CDF PYTHIA 6.2 Tune DW predictions of the LHC underlying event (UE) data at 900 GeV and 7 TeV are examined in detail. The behavior of the UE at the LHC is roughly what we expected. The new LHC PYTHIA 6.4 Tune Z1 does an even better job…

Edge machine learning involves the deployment of learning algorithms at the network edge to leverage massive distributed data and computation resources to train artificial intelligence (AI) models. Among others, the framework of federated…

Data Loss/Leakage Prevention (DLP) continues to be the main issue for many large organizations. There are multiple numbers of emerging security attach scenarios and a limitless number of overcoming solutions. Today's enterprises' major…

In this article we describe the migration of event data collected by the COMPASS and HARP experiments at CERN. Together these experiments have over 300TB of physics data stored in Objectivity/DB that had to be transferred to a new data…

The process e^+e^- -> gamma gamma (gamma) is studied using data recorded with the OPAL detector at LEP. The data sample corresponds to a total integrated luminosity of 25.38 pb^{-1} taken at centre-of-mass energies of 130-172 GeV. The…

Selected topics on precision tests of the Standard Model of the Electroweak and the Strong Interaction at the LEP $e^+e^-$ collider are presented, including an update of the world summary of measurements of $\alpha_s$, representing the…

This paper addresses the critical challenge of estimating the reliability of an Electric Vehicle (EV) charging systems when facing risks such as overheating, unpredictable, weather, and cyberattacks. Traditional methods for predicting…

Electronic health record (EHR) data are increasingly used to support real-world evidence (RWE) studies. Yet its ability to generate reliable RWE is limited by the lack of readily available precise information on the timing of clinical…

We introduce a new measure to evaluate the transferability of representations learned by classifiers. Our measure, the Log Expected Empirical Prediction (LEEP), is simple and easy to compute: when given a classifier trained on a source data…