Search results for "federated"
showing 10 items of 12 documents
Edge Computing-enabled Intrusion Detection for C-V2X Networks using Federated Learning
2022
Intrusion detection systems (IDS) have already demonstrated their effectiveness in detecting various attacks in cellular vehicle-to-everything (C-V2X) networks, especially when using machine learning (ML) techniques. However, it has been shown that generating ML-based models in a centralized way consumes a massive quantity of network resources, such as CPU/memory and bandwidth, which may represent a critical issue in such networks. To avoid this problem, the new concept of Federated Learning (FL) emerged to build ML-based models in a distributed and collaborative way. In such an approach, the set of nodes, e.g., vehicles or gNodeB, collaborate to create a global ML model trained across thes…
Model independent assertions for integration of heterogeneous schemas
1992
Due to the proliferation of database applications, the integration of existing databases into a distributed or federated system is one of the major challenges in responding to enterprises' information requirements. Some proposed integration techniques aim at providing database administrators (DBAs) with a view definition language they can use to build the desired integrated schema. These techniques leave to the DBA the responsibility of appropriately restructuring schema elements from existing local schemas and of solving inter-schema conflicts. This paper investigates the assertion-based approach, in which the DBA's action is limited to pointing out corresponding elements in the schemas an…
A novel approach towards skill-based search and services of Open Educational Resources
2011
Open educational resources (OER) have a high potential to address the growing need for training materials in management education and training. Today, a high number of OER in management are already available in a large number of repositories. However, users face barriers as they have to search repository by repository with different interfaces to retrieve the appropriate learning content. In addition, the use of search criteria related to skills, such as learning objectives and skill-levels is not generally supported. The European co-funded project OpenScout addresses these barriers by intelligently connecting leading European OER repositories and providing federated, skillbased search and …
Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement s…
2017
© 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground Underweight, overweight, and obesity in childhood and adolescence are associated with adverse health consequences throughout the life-course. Our aim was to estimate worldwide trends in mean body-mass index (BMI) and a comprehensive set of BMI categories that cover underweight to obesity in children and adolescents, and to compare trends with those of adults. Methods We pooled 2416 population-based studies with measurements of height and weight on 128·9 million participants aged 5 years and older, including 31·5 million aged 5–19 years. We used a Bayesian hierarchical model …
Skill-Based Scouting of Open Management Content
2010
Already existing open educational resources in management have a high potential for enterprises to address the increasing training needs of their employees. However, access barriers still prevent the full exploitation of this potential. Users have to search a number of repositories with heterogeneous interfaces in order to retrieve the desired content. In addition, the use of search criteria related to skills, such as learning objectives and skill-levels is in most cases not supported. The demonstrator presented in this paper addresses these shortcomings by federating multiple repositories, integrating and enriching their metadata, and employing skill-based search for management related con…
A Federated Learning Approach for Distributed Human Activity Recognition
2022
In recent years, the widespread diffusion of smart pervasive devices able to provide AI-based services has encouraged research in the definition of new distributed learning paradigms. Federated Learning (FL) is one of the most recent approaches which allows devices to collaborate to train AI-based models, whereas guarantying privacy and lower communication costs. Although different studies on FL have been conducted, a general and modular architecture capable of performing well in different scenarios is still missing. Following this direction, this paper proposes a general FL framework whose validity is assessed by considering a distributed activity recognition scenario in which users' perso…
Influence of Psychological Factors in Federated Futsal and Lifeguard Athletes, Differences by Gender and Category
2021
This research aims to analyse the differences in optimism, resilience, engagement and competitive anxiety as a function of the sport modality practiced in lifeguarding (individual sport) and futsal (team sport); the sport category by age (cadet or youth) and gender. The LOT-R optimism questionnaire, the Connor-Davidson Resilience Scale (CD-RISC-10), the Utrecht Work Engagement Scale (UWES) and the Competitive Anxiety Scale (SAS-2) were applied to a sample of 189 participants (139 men and 50 womwn) aged between 14 and 17 years. The following statistical tests are performed: Cronbach's alpha, Pearson's linear correlation, Student's t-test, Kolmogorov-Smirnov test, Levene's test and multivaria…
Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks
2023
Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of advanced machine/deep learning-based solutions have been designed to accurately detect security attacks. Specifically, supervised learning techniques have been widely applied to train attack detection models. However, the main limitation of such solutions is their inability to detect attacks different from those seen during the training phase, or new attacks, also called zero-day attacks. Moreover, training the detection model requires significant data collection and labeling, which increases th…
FOWLA, A Federated Architecture for Ontologies.
2015
International audience; The progress of information and communication technologies has greatly increased the quantity of data to process. Thus, managing data heterogeneity is a problem nowadays. In the 1980s, the concept of a Federated Database Architecture (FDBA) was introduced as a collection of components to unite loosely coupled federation. Semantic web technologies mitigate the data heterogeneity problem, however due to the data structure heterogeneity the integration of several ontologies is still a complex task. For tackling this problem, we propose a loosely coupled federated ontology architecture (FOWLA). Our approach allows the coexistence of various ontologies sharing common data…
A Federated Approach for Interoperating AEC/FM Ontologies
2016
International audience; Over the last few years, the benefits of applying ontologies (semantic graph modelling) for Architecture, Engineering, Construction and Facility Management (AEC/FM) industry have been recognized by several researchers and industry stakeholders. One of the main motivations is because it eases AEC data manipulation and representation. However, a research question that still remains open is how to take advantage of semantic web technologies to interoperate the AEC/FM and other ontologies in a flexible and dynamical way in order to solve data structure heterogeneity problem. Because of this, we propose in this paper to apply a rule-based federated architecture to answer …