Search results for "LAB"
showing 10 items of 7932 documents
Retinal Fundus Multi-Disease Image Dataset (RFMiD): A Dataset for Multi-Disease Detection Research
2021
The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. Early detection and diagnosis of ocular pathologies would enable forestall of visual impairment. One challenge that limits the adoption of computer-aided diagnosis tool by ophthalmologists is the number of sight-threatening rare pathologies, such as central retinal artery occlusion or anterior ischemic optic neuropathy, and others are usually ignored. In the past two decades, many publicly available datasets of color fundus images have been collected with a primary focus on diabetic retinopathy, glaucoma, age-related macular…
A Two-layer Partitioning for Non-point Spatial Data
2021
Non-point spatial objects (e.g., polygons, linestrings, etc.) are ubiquitous and their effective management is always timely. We study the problem of indexing non-point objects in memory. We propose a secondary partitioning technique for space-oriented partitioning indices (e.g., grids), which improves their performance significantly, by avoiding the generation and elimination of duplicate results. Our approach is novel and of a high impact, as (i) it is extremely easy to implement and (ii) it can be used by any space-partitioning index. We show how our approach can be used to boost the performance of spatial range queries. We also show how we can avoid performing the expensive refinement s…
Multiple UAV cooperative path planning via neuro-dynamic programming
2004
In this paper, a team of n unmanned air-vehicles (UAVs) in cooperative path planning is given the task of reaching the assigned target while i) avoiding threat zones ii) synchronizing minimum time arrivals on the target, and iii) ensuring arrivals coming from different directions. We highlight three main contributions. First we develop a novel hybrid model and suit it to the problem at hand. Second, we design consensus protocols for the management of information. Third, we synthesize local predictive controllers through a distributed, scalable and suboptimal neuro-dynamic programming (NDP) algorithm.
Insights on Partial Information Sharing in Supply Chain dynamics
2015
This paper provides an assessment of partial Information Sharing (IS) in Supply Chain (SC). We study the dynamics of collaborative multi-echelon structure, characterized by an increasing level of information visibility among partners. To do so, we mathematically model six four-echelon serial SCs via difference equations and conduct numerical simulations on the basis of a robust design of experiment. Results shows how (1) as the extent of IS increases, the performance of whole SC improves as well, and (2) the impact of IS depends not on which particular members are involved but on the number of collaborative members.
The Evolution of Blockchain Virtual Machine Architecture Towards an Enterprise Usage Perspective
2019
Virtualization in the context of blockchain systems represents an essential phase in the development and migration of services from public chains to enterprise logic. Most of the ongoing blockchain uses-cases are using the existing public ledgers, but for business products and services, there is a need for custom tailored solutions to ensure flexibility and security. The Ethereum Virtual Machine has opened new ways to solve problems that require a public proof by executing logic on a decentralized ecosystem. In a natural evolutive process, virtualization logic was shaped by numerous architectures and business requirements. Beside performance and scalability, enterprise virtual machines are …
Distributed Coverage of Ego Networks in F2F Online Social Networks
2016
Although most online social networks rely on a centralized infrastructure, several proposals of Distributed Online Social Networks (DOSNs) have been recently presented. Since in DOSNs user profiles are stored on the peers of the users belonging to the network, one of the main challenges comes from guaranteeing the profile availability when the owner of the data is not online. In this paper, we propose a DOSN based on a friend-to-friend P2P overlay where the user's data is stored only on friend peers. Our approach is based on the ego-network concept, which models the social network from the local point of view of a single user. We propose a distributed algorithm which is based on the notion …
Privacy and temporal aware allocation of data in decentralized online social networks
2017
Distributed Online Social Networks (DOSNs) have recently been proposed to grant users more control over the data they share with the other users. Indeed, in contrast to centralized Online Social Networks (such as Facebook), DOSNs are not based on centralized storage services, because the contents shared by the users are stored on the devices of the users themselves. One of the main challenges in a DOSN comes from guaranteeing availability of the users' contents when the data owner disconnects from the network. In this paper, we focus our attention on data availability by proposing a distributed allocation strategy which takes into account both the privacy policies defined on the contents an…
An Efficient and Secure Multidimensional Data Aggregation for Fog-Computing-Based Smart Grid
2021
International audience; The secure multidimensional data aggregation (MDA) has been widely investigated in smart grid for smart cities. However, previous proposals use heavy computation operations either to encrypt or to decrypt the multidimensional data. Moreover, previous fault-tolerant mechanisms lead to an important computation cost, and also a high communication cost when considering a separate identification phase. In this article, we propose an efficient and secure MDA scheme, named ESMA. Unlike existing schemes, the multidimensional data in ESMA are structured and encrypted into a single Paillier ciphertext and thereafter, the data are efficiently decrypted. For privacy preserving, …
An approach based on the Adaptive Resonance Theory for analysing the viability of recommender systems in a citizen Web portal
2007
This paper proposes a methodology to optimise the future accuracy of a collaborative recommender application in a citizen Web portal. There are four stages namely, user modelling, benchmarking of clustering algorithms, prediction analysis and recommendation. The first stage is to develop analytical models of common characteristics of Web-user data. These artificial data sets are then used to evaluate the performance of clustering algorithms, in particular benchmarking the ART2 neural network with K-means clustering. Afterwards, it is evaluated the predictive accuracy of the clusters applied to a real-world data set derived from access logs to the citizen Web portal Infoville XXI (http://www…