Search results for "Detection"
showing 10 items of 2543 documents
Evaluation of Ensemble Machine Learning Methods in Mobile Threat Detection
2017
The rapid growing trend of mobile devices continues to soar causing massive increase in cyber security threats. Most pervasive threats include ransom-ware, banking malware, premium SMS fraud. The solitary hackers use tailored techniques to avoid detection by the traditional antivirus. The emerging need is to detect these threats by any flow-based network solution. Therefore, we propose and evaluate a network based model which uses ensemble Machine Learning (ML) methods in order to identify the mobile threats, by analyzing the network flows of the malware communication. The ensemble ML methods not only protect over-fitting of the model but also cope with the issues related to the changing be…
Assessment of Deep Learning Methodology for Self-Organizing 5G Networks
2019
In this paper, we present an auto-encoder-based machine learning framework for self organizing networks (SON). Traditional machine learning approaches, for example, K Nearest Neighbor, lack the ability to be precisely predictive. Therefore, they can not be extended for sequential data in the true sense because they require a batch of data to be trained on. In this work, we explore artificial neural network-based approaches like the autoencoders (AE) and propose a framework. The proposed framework provides an advantage over traditional machine learning approaches in terms of accuracy and the capability to be extended with other methods. The paper provides an assessment of the application of …
Contact Estimation in Robot Interaction
2014
In the paper, safety issues are examined in a scenario in which a robot manipulator and a human perform the same task in the same workspace. During the task execution, the human should be able to physically interact with the robot, and in this case an estimation algorithm for both interaction forces and a contact point is proposed in order to guarantee safety conditions. The method, starting from residual joint torque estimation, allows both direct and adaptive computation of the contact point and force, based on a principle of equivalence of the contact forces. At the same time, all the unintended contacts must be avoided, and a suitable post-collision strategy is considered to move the r…
Automated detection of lung nodules in low-dose computed tomography
2007
A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector computed-tomography (CT) images has been developed in the framework of the MAGIC-5 Italian project. One of the main goals of this project is to build a distributed database of lung CT scans in order to enable automated image analysis through a data and cpu GRID infrastructure. The basic modules of our lung-CAD system, consisting in a 3D dot-enhancement filter for nodule detection and a neural classifier for false-positive finding reduction, are described. The system was designed and tested for both internal and sub-pleural nodules. The database used in this study consists of 17 low…
Simulating quantum-optical phenomena with optical lattices
2011
Cold atoms trapped in optical lattices have been proved to be very versatile quantum systems in which a large class of many-body condensed-matter Hamiltonians can be simulated [1].
Parallelization of a Lattice Boltzmann Suspension Flow Solver
2002
We have applied a parallel Lattice Boltzmann method to solve the behaviour of the suspension flow. The complex behaviour of the suspension flow cannot be solved by analytical methods, so simulations are the only way to study it. Usually the size of an interesting problem is so big that calculation time on one processor is too long, and this can be solved by parallel program. We have written a parallel suspension flow solver and tested it on massive parallel computers. The measured performance of our program show that the parallelization of suspension particles was successful. We also show that over one million particles can be simulated.
A glassy carbon electrode modified by a triply-fused-like Co( ii ) polyporphine and its ability for sulphite oxidation and detection
2018
This article presents a Co(II) polyporphine conductive polymer easily and rapidly obtained (less than 2 h 30 min) on the surface of a glassy carbon electrode from the transformation of an initial Mg(II) porphine solution in a four-step process (including electrochemical and chemical stages). The intimate molecular structure is argued on the basis of the electrochemical response of the modified electrode, as well as its surface characterization. Owing to its apparent stability in water over potential cycling and its high density in active Co(II) centers, the electrosynthesized film shows its ability to catalyze sulphite oxidation in aqueous solutions. The mechanism of this molecular catalysi…
Wavelet analysis of human photoreceptoral response
2010
Feature detection of biomedical signals is crucial for deepening our knowledge of the physiological phenomena giving rise to them. To achieve this aim, even if many analytic approaches have been suggested only few are able to deal with signals whose features are time dependent, and to provide useful clinical information. In this work we use the wavelet analysis to extract peculiarities of the early response of the photoreceptoral human system, known as a-wave ERG-component. The analysis of the a-wave features is important since this component reflects the functional integrity of the two populations of photoreceptors, rods and cones whose activation dynamics are not well known. Moreover, in …
On the Robust Synthesis of Logical Consensus Algorithms for Distributed Intrusion Detection
2013
We introduce a novel consensus mechanism by which the agents of a network can reach an agreement on the value of a shared logical vector function depending on binary input events. Based on results on the convergence of finite--state iteration systems, we provide a technique to design logical consensus systems that minimize the number of messages to be exchanged and the number of steps before consensus is reached, and that can tolerate a bounded number of failed or malicious agents. We provide sufficient joint conditions on the input visibility and the communication topology for the method's applicability. We describe the application of our method to two distributed network intrusion detecti…
Towards a Non-Intrusive Context-Aware Speech Quality Model
2020
Understanding how humans judge perceived speech quality while interacting through Voice over Internet Protocol (VoIP) applications in real-time is essential to build a robust and accurate speech quality prediction model. Speech quality is degraded in the presence of background noise reducing the Quality of Experience (QoE). Speech Enhancement (SE) algorithms can improve speech quality in noisy environments. The publicly available NOIZEUS speech corpus contains speech in environmental background noise babble, car, street, and train at two Signal-to-noise ratio (SNRs) 5dB and 10dB. Objective Speech Quality Metrics (OSQM) are used to monitor and measure speech quality for VoIP applications. Th…