Search results for "Software"
showing 10 items of 7396 documents
Blockchain based Inter-domain Latency Aware Routing Proposal in Software Defined Network
2018
Border gateway protocol (BGP) version 4 is routing current Internet for more than 20 years. BGP is the only protocol that has proven its routing capability of such size network with continually growing nature. Although BGP is scalable and network layer reachability information it lacks quality of service metrics like latency. BGP routing decision algorithm uses as-path length between autonomous systems (AS) as main factor for most of its best-path calculations. Because of more affordable peering architectures as-path length is generally decreasing in worldwide internet network resulting in less efficient routes for real-time internet protocol traffic. This study proposes future internet arc…
Dynamic Modeling of the Cyber Security Threat Problem
2009
This chapter discusses the possible growth of black markets (BMs) for software vulnerabilities and factors affecting their spread. It is difficult to collect statistics about BMs for vulnerabilities and their associated transactions, as they are hidden from general view. We conduct a disguised observation of online BM trading sites to identify causal models of the ongoing viability of BMs. Our observation results are expressed as a system dynamic model. We implement simulations to observe the effects of possible actions to disrupt BMs. The results suggest that without interventions the number and size of BMs is likely to increase. A simulation scenario with a policy to halt BM operations re…
Applying logistic regression to relevance feedback in image retrieval systems
2007
This paper deals with the problem of image retrieval from large image databases. A particularly interesting problem is the retrieval of all images which are similar to one in the user's mind, taking into account his/her feedback which is expressed as positive or negative preferences for the images that the system progressively shows during the search. Here we present a novel algorithm for the incorporation of user preferences in an image retrieval system based exclusively on the visual content of the image, which is stored as a vector of low-level features. The algorithm considers the probability of an image belonging to the set of those sought by the user, and models the logit of this prob…
A Conversational Agent Based on a Conceptual Interpretation of a Data Driven Semantic Space
2005
In this work we propose an interpretation of the LSA framework which leads to a data-driven “conceptual” space creation suitable for an “intuitive” conversational agent. The proposed approach allows overcoming the limitations of traditional, rule-based, chat-bots, leading to a more natural dialogue.
A word prediction methodology for automatic sentence completion
2015
Word prediction generally relies on n-grams occurrence statistics, which may have huge data storage requirements and does not take into account the general meaning of the text. We propose an alternative methodology, based on Latent Semantic Analysis, to address these issues. An asymmetric Word-Word frequency matrix is employed to achieve higher scalability with large training datasets than the classic Word-Document approach. We propose a function for scoring candidate terms for the missing word in a sentence. We show how this function approximates the probability of occurrence of a given candidate word. Experimental results show that the proposed approach outperforms non neural network lang…
A family of kernel anomaly change detectors
2014
This paper introduces the nonlinear extension of the anomaly change detection algorithms in [1] based on the theory of reproducing kernels. The presented methods generalize their linear counterparts, under both the Gaussian and elliptically-contoured assumptions, and produce both improved detection accuracies and reduced false alarm rates. We study the Gaussianity of the data in Hilbert spaces with kernel dependence estimates, provide low-rank kernel versions to cope with the high computational cost of the methods, and give prescriptions about the selection of the kernel functions and their parameters. We illustrate the performance of the introduced kernel methods in both pervasive and anom…
Validation of a Reinforcement Learning Policy for Dosage Optimization of Erythropoietin
2007
This paper deals with the validation of a Reinforcement Learning (RL) policy for dosage optimization of Erythropoietin (EPO). This policy was obtained using data from patients in a haemodialysis program during the year 2005. The goal of this policy was to maintain patients' Haemoglobin (Hb) level between 11.5 g/dl and 12.5 g/dl. An individual management was needed, as each patient usually presents a different response to the treatment. RL provides an attractive and satisfactory solution, showing that a policy based on RL would be much more successful in achieving the goal of maintaining patients within the desired target of Hb than the policy followed by the hospital so far. In this work, t…
The dynamics over the next few years of the Spanish mobile telecommunications market share: a mathematical modelling approach
2013
Taking into account available data from 2002 to 2009 about the market share percentages of the Spanish mobile telecommunications service providers, a dynamic diffusion model to study the evolution of the clients’ change between the different companies during the period 2010–2016 is proposed. The constructed model provides a tool for forecasting short-term trends about the customers’ preferences with respect to mobile network operators taking into account both, autonomous decisions due to direct marketing and advertising strategies, and also decisions adopted through interaction via social influence. The model can provide insights to companies for designing strategies in order to gain market…