A5101910005- Distributed and Parallel Computing Systems
- Advanced Data Storage Technologies
- Behavioral Health and Interventions
- Physical Activity and Health
- Network Security and Intrusion Detection
- Service-Oriented Architecture and Web Services
- Data Management and Algorithms
- Scientific Computing and Data Management
- Anomaly Detection Techniques and Applications
- Cloud Computing and Resource Management
- Freedom of Expression and Defamation
- Intellectual Property Law
- Superconducting Materials and Applications
- Mobile Agent-Based Network Management
- Hate Speech and Cyberbullying Detection
- Scheduling and Optimization Algorithms
- Space exploration and regulation
- Space Science and Extraterrestrial Life
- Ship Hydrodynamics and Maneuverability
- Algorithms and Data Compression
- Particle Accelerators and Free-Electron Lasers
- Defense, Military, and Policy Studies
- Neural Networks and Applications
- Software System Performance and Reliability
- Complex Network Analysis Techniques
European Organization for Nuclear Research
2014-2024
Queen's University Belfast
2011-2020
University of Kansas
2020
Medical Research Council
2015
Chinese University of Hong Kong
2015
University of Hong Kong
2015
University of Ulster
2013
Royal Victoria Hospital
2013
University of Missouri Hospital
2007
University of Alabama
2005
We investigated whether "hidden" (or unobserved) social networks were evident in a 2011 physical activity behavior change intervention Belfast, Northern Ireland. Results showed evidence of unobserved the and illustrated how network evolved over short periods affected behavior. Behavior interventions should account for interaction among participants (i.e., networks) such interactions affect outcome.
This paper presents Yagada, an algorithm to search labelled graphs for anomalies using both structural data and numeric attributes. Yagada is explained several security-related examples validated with experiments on a physical Access Control database. Quantitative analysis shows that in the upper range of anomaly thresholds, detects twice as many best-performing discretization algorithm. Qualitative evaluation detected are meaningful, representing combination irregularities numerical outliers.
The goal of the HTTP REST API for Tape project is to provide a simple, minimalistic and uniform interface manage data transfers between Storage Endpoints (SEs) where source file on tape. collaboration developers WLCG storage systems (EOS+CTA, dCache, StoRM) transfer clients (gfal2, FTS). For some years, has been growing in popularity as preferred protocol many SEs. However — unlike other protocols such XRootD SRM does not include method stage files from tape disk prior transfer, forcing use...
The CERN Tape Archive (CTA) is the successor to CASTOR and tape backend EOS. It was designed meet needs of archival storage data from LHC Run–3 other experimental programmes at CERN. In wider Worldwide Computing Grid (WLCG), software landscape quite heterogeneous, but we are entering a period consolidation. A number sites have reevaluated their options choosing CTA for future needs. However, CTA’s original mandate imposed several design constraints which not necessarily optimal external...
During 2019 and 2020, the CERN tape archive (CTA) will receive new data from LHC experiments import existing CASTOR, which be phased out for before Run 3. This contribution present statuses of CTA as a service its integration with EOS FTS flow chains experiments. The latest enhancements additions to software well development outlook presented. With repack function, necessary behind-the-scenes feature, can now take over custodial handle media migration, compaction failures. Further metadata...
The first production version of the CERN Tape Archive (CTA) software is planned to be released during 2019. CTA designed replace CASTOR as tape archive solution, face scalability and performance challenges arriving with LHC Run–3. In this paper, we describe main commonalities differences between CASTOR. We outline functional enhancements integration steps required add back-end an EOS disk storage system. present discuss different deployment migration scenarios for replacing five instances at...
The CERN Tape Archive (CTA) provides a tape backend to disk systems and, in conjunction with EOS, is managing the data of LHC experiments at CERN. Magnetic storage offers lowest cost per unit volume today, followed by hard disks and flash. In addition, current drives deliver solid bandwidth (typically 360MB/s device), but high latencies, both for mounting drive positioning when accessing non-adjacent files. As consequence, transfer scheduler should queue requests before warranting mount...
Cloud computing has been heralded as a new era in the evolution of information and communications technologies. ICT giants have invested heavily developing technologies mega server facilities, which allow end users to access web-based software applications store their data off-site. Businesses using cloud services will benefit from reduced operating costs they cut back on infrastructure personnel. Individuals no longer need buy install universal through any internet-ready device. Yet, hidden...
The EOS disk + CERN Tape Archive (EOSCTA) service is CERN’s primary physics data long-term storage and archival solution for LHC Run 3. It entered production at during summer 2020 has since been serving all the non-LHC workflows involving to-and retrieval from tape. CTA system a complete redesign of previous tape software, cache workflows, which will need to scale rate requirements present activity period, as well one after. At time writing it already set new records monthly volume reached...
Generative algorithms for random graphs have yielded insights into the structure and evolution of real-world networks. Most networks exhibit a well-known set properties, such as heavy-tailed degree distributions, clustering community formation. Usually, graph models consider only structural information, but many also labelled vertices weighted edges. In this paper, we present generative model with discrete vertex labels numeric edge weights. The weights are represented Beta Mixture Models...