Search results for " machine"
showing 10 items of 1317 documents
Towards a SDN-based architecture for analyzing network traffic in cloud computing infrastructures
2015
Currently, network traffic monitoring tools do not fit well in the monitoring of cloud computing infrastructures. These tools are not integrated with the control plane of the cloud computing stack. This lack of integration causes a deficiency in the handling of the re-usage of IP addresses along virtual machines, a lack of adaption and reaction on highly frequent topology changes, and a lack of accuracy in the metrics gathered for the networking traffic flowing along the cloud infrastructure. The main contribution of this paper is to provide a novel SDN-based architecture to carry out the monitoring of network traffic in cloud infrastructures. The architecture in based on the integration be…
Review of web-based information security threats in smart grid
2017
The penetration of digital devices in Smart Grid has created a big security issue. OWASP is an online community of security professionals that identifies the most critical web application security risk in IT domain. Smart Grid also uses client-server based web-applications to collect and disseminate information. Therefore, Smart Grid network is analogous to IT network and similar kind of risk exists in the Smart Grid. This paper review the security risk in Smart Grid domain with reference to OWASP study. The Smart Grid security is more biased towards vulnerabilities associated with a machine to machine communication. Methodology to minimise the risk of attack is also discussed in this resea…
Convolutional Long Short-Term Memory Network for Multitemporal Cloud Detection Over Landmarks
2019
In this work, we propose to exploit both the temporal and spatial correlations in Earth observation satellite images through deep learning methods. In particular, the combination of a U-Net convolutional neural network together with a convolutional long short-term memory (LSTM) layer is proposed. This model is applied for cloud detection on MSG/SEVIRI image time series over selected landmarks. Implementation details are provided and our proposal is compared against a standard SVM and a U-Net without the convolutional LSTM layer but including temporal information too. Experimental results show that this combination of networks exploits both the spatial and temporal dependence and provides st…
Psychological Influence of Double-Bind Situations in Human-Agent Interaction
2007
This paper presents a new approach to integrate artificial intelligence in virtual environments. The system presented deals in a separated way the visualization and intelligence modules, applying in this last case a distributed approach (multi-agent systems) so that scalable applications may be built. Therefore, it is necessary to define agent architectures that allow agents to be integrated in the VW. Thus, a designer is abstracted from the peculiarities of interacting with a virtual environment. There is a first prototype of the framework using JADE as the supporting multi-agent systems platform.
Extracting information from support vector machines for pattern-based classification
2014
Statistical machine learning algorithms building on patterns found by pattern mining algorithms have to cope with large solution sets and thus the high dimensionality of the feature space. Vice versa, pattern mining algorithms are frequently applied to irrelevant instances, thus causing noise in the output. Solution sets of pattern mining algorithms also typically grow with increasing input datasets. The paper proposes an approach to overcome these limitations. The approach extracts information from trained support vector machines, in particular their support vectors and their relevance according to their coefficients. It uses the support vectors along with their coefficients as input to pa…
Full Reference Mesh Visual Quality Assessment Using Pre-Trained Deep Network and Quality Indices
2019
In this paper, we propose an objective quality metric to evaluate the perceived visual quality of 3D meshes. Our method relies on pre-trained convolutional neural network i.e VGG to extract features from the distorted mesh and its reference. Quality indices from well-known mesh visual quality metrics are concatenated with the extracted features resulting a global feature vector. this latter is used to learn the support vector regression (SVR) to predict the final quality score. Experimental results from two subjective databases (LIRIS masking database and LIRIS/EPFL general-purpose database) and comparisons with seven objective metrics cited in the state-of-the-art demonstrate the effective…
An adaptive probabilistic approach to goal-level imitation learning
2010
Imitation learning has been recognized as a promising technique to teach robots advanced skills. It is based on the idea that robots could learn new behaviors by observing and imitating the behaviors of other skilled actors. We propose an adaptive probabilistic graphical model which copes with three core issues of any imitative behavior: observation, representation and reproduction of skills. Our model, Growing Hierarchical Dynamic Bayesian Network (GHDBN), is hierarchical (i.e. able to characterize structured behaviors at different levels of abstraction), and growing (i.e. skills are learned or updated incrementally - and at each level of abstraction - every time a new observation sequence…
A Support Vector Machine Signal Estimation Framework
2018
Support vector machine (SVM) were originally conceived as efficient methods for pattern recognition and classification, and the SVR was subsequently proposed as the SVM implementation for regression and function approximation. Nowadays, the SVR and other kernel‐based regression methods have become a mature and recognized tool in digital signal processing (DSP). This chapter starts to pave the way to treat all the problems within the field of kernel machines, and presents the fundamentals for a simple, framework for tackling estimation problems in DSP using support vector machine SVM. It outlines the particular models and approximations defined within the framework. The chapter concludes wit…
Location-Aware Mobile Intrusion Detection with Enhanced Privacy in a 5G Context
2010
Published version of an article from the journal: Wireless Personal Communications. The original publication is available at Spingerlink. http://dx.doi.org/10.1007/s11277-010-0069-6 The paper proposes a location-aware mobile Intrusion Prevention System (mIPS) architecture with enhanced privacy that is integrated in Managed Security Service (MSS). The solution is envisaged in a future fifth generation telecommunications (5G) context with increased but varying bandwidth, a virtualised execution environment and infrastructure that allows threads, processes, virtual machines and storage to be migrated to cloud computing services on demand, to dynamically scale performance and save power. 5G mob…
On the Characterization of Distributed Virtual Environment Systems
2003
Distributed Virtual Environment systems have experienced a spectacular growth last years. One of the key issues in the design of scalable and cost-effective DVE systems is the partitioning problem. This problem consists of efficiently assigning clients (3-D avatars) to the servers in the system, and some techniques have been already proposed for solving it.