Search results for "Networks"
showing 10 items of 3260 documents
Efficient FPGA Implementation of a Knowledge-Based Automatic Speech Classifier
2005
Speech recognition has become common in many application domains, from dictation systems for professional practices to vocal user interfaces for people with disabilities or hands-free system control. However, so far the performance of Automatic Speech Recognition (ASR) systems are comparable to Human Speech Recognition (HSR) only under very strict working conditions, and in general far lower. Incorporating acoustic-phonetic knowledge into ASR design has been proven a viable approach to rise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as dete…
Application of EαNets to Feature Recognition of Articulation Manner in Knowledge-Based Automatic Speech Recognition
2006
Speech recognition has become common in many application domains. Incorporating acoustic-phonetic knowledge into Automatic Speech Recognition (ASR) systems design has been proven a viable approach to rise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as detectors for manner of articulation attributes starting from representations of speech signal frames. In this paper, a set of six detectors for the above mentioned attributes is designed based on the E-αNet model of neural networks. This model was chosen for its capability to learn hidden acti…
A Reconfigurable Neural Environment on Active Networks
2000
This paper proposes the deployment of a neural network computing environment on Active Networks. Active Networks are packet-switched computer networks in which packets can contain code fragments that are executed on the intermediate nodes. This feature allows the injection of small pieces of codes to deal with computer network problems directly into the network core, and the adoption of new computing techniques to solve networking problems. The goal of our project is the adoption of a distributed neural network for approaching tasks which are specific of the computer network environment. Dynamically reconfigurable neural networks are spread on an experimental wide area backbone of active no…
A Novel Recruitment Policy to Defend against Sybils in Vehicular Crowdsourcing
2021
Vehicular Social Networks (VSNs) is an emerging communication paradigm, derived by merging the concepts of Online Social Networks (OSNs) and Vehicular Ad-hoc Networks (VANETs). Due to the lack of robust authentication mechanisms, social-based vehicular applications are vulnerable to numerous attacks including the generation of sybil entities in the networks. We address this important issue in vehicular crowdsourcing campaigns where sybils are usually employed to increase their influence and worsen the functioning of the system. In particular, we propose a novel User Recruitment Policy (URP) that, after extracting the participants within the event radius of a crowdsourcing campaign, detects …
Assessing Coastal Sustainability: A Bayesian Approach for Modeling and Estimating a Global Index for Measuring Risk
2013
Integrated Coastal Zone Management is an emerg- ing research area. The aim is to provide a global view of dif- ferent and heterogeneous aspects interacting in a geographical area. Decision Support Systems, integrating Computational Intelligence methods, can be successfully used to estimate use- ful anthropic and environmental indexes. Bayesian Networks have been widely used in the environmental science domain. In this paper a Bayesian model for estimating the Sustainable Coastal Index is presented. The designed Bayesian Network consists of 17 nodes, hierarchically organized in 4 layers. The first layer is initialized with the season and the physiographic region information. In the second la…
EMBER—Embedding Multiple Molecular Fingerprints for Virtual Screening
2022
In recent years, the debate in the field of applications of Deep Learning to Virtual Screening has focused on the use of neural embeddings with respect to classical descriptors in order to encode both structural and physical properties of ligands and/or targets. The attention on embeddings with the increasing use of Graph Neural Networks aimed at overcoming molecular fingerprints that are short range embeddings for atomic neighborhoods. Here, we present EMBER, a novel molecular embedding made by seven molecular fingerprints arranged as different “spectra” to describe the same molecule, and we prove its effectiveness by using deep convolutional architecture that assesses ligands&…
BioAnalysis: A Framework for Structural and Functional Robustness Analysis of Metabolic Networks
2010
The main objective of this work is to analyze metabolic networks evolution in terms of their robustness and fault tolerance capabilities. In metabolic networks, errors can be seen as random removal of network nodes, while attacks are high-connectivity-degree node deletion aimed at compromising network activity. This paper proposes a software framework, namely BioAnalysis, used to test the robustness and the fault tolerance capabilities of real metabolic networks, when mutations and node deletions affect the network structure. The performed simulations are related to the central metabolic network of the well-known E. coli single-celled bacterium and involve either hub nodes or non-hub nodes,…
METABOLIC NETWORKS ROBUSTNESS: THEORY, SIMULATIONS AND RESULTS
2011
Metabolic networks are composed of several functional modules, reproducing metabolic pathways and describing the entire cellular metabolism of an organism. In the last decade, an enormous interest has grown for the study of tolerance to errors and attacks in metabolic networks. Studies on their robustness have suggested that metabolic networks are tolerant to errors, but very vulnerable to targeted attacks against highly connected nodes. However, many findings on metabolic networks suggest that the above classification is too simple and imprecise, since hub node attacks can be by-passed if alternative metabolic paths can be exploited. On the contrary, non-hub nodes attacks can affect cell …
Copy–Move Forgery Detection by Matching Triangles of Keypoints
2015
Copy-move forgery is one of the most common types of tampering for digital images. Detection methods generally use block-matching approaches, which first divide the image into overlapping blocks and then extract and compare features to find similar ones, or point-based approaches, in which relevant keypoints are extracted and matched to each other to find similar areas. In this paper, we present a very novel hybrid approach, which compares triangles rather than blocks, or single points. Interest points are extracted from the image, and objects are modeled as a set of connected triangles built onto these points. Triangles are matched according to their shapes (inner angles), their content (c…
SecureBallot: A secure open source e-Voting system
2021
Abstract Voting is one of the most important acts through which a community can make a collective decision. In recent years, many works have focused on improving traditional voting mechanisms and, as a result, a wide range of electronic voting (e-Voting) systems have been proposed. Even though some approaches have achieved a proper level of usability, the main challenges of e-Voting are essentially still open: protect the privacy of participants, guarantee secrecy, anonymity, integrity, uniqueness, and authenticity of votes, while making e-Voting as trustful as voting. In order to address this issue, we present SecureBallot, a secure open-source e-Voting system that completely decouples the…