Analytical study of coherence in seeded modulation instability

We derive analytical expressions for the coherence in the onset of modulation instability, in excellent agreement with thorough numerical simulations. As usual, we start by a linear perturbation analysis, where broadband noise is added to a continuous wave (CW) pump; then, we investigate the effect of adding a deterministic seed to the CW pump, a case of singular interest as it is commonly encountered in parametric amplification schemes. Results for the dependence of coherence on parameters such as fiber type, pump power, propagated distance, seed signal-to-noise ratio are presented. Finally, we show the importance of including higher-order linear and nonlinear dispersion when dealing with generation in longer wavelength regions (mid IR). We believe these results to be of relevance when applied to the analysis of the coherence properties of supercontinua generated from CW pumps.Comment: 6 pages, 8 figure

On the beneficial role of noise in resistive switching

We study the effect of external noise on resistive switching. Experimental results on a manganite sample are presented showing that there is an optimal noise amplitude that maximizes the contrast between high and low resistive states. By means of numerical simulations, we study the causes underlying the observed behavior. We find that experimental results can be related to general characteristics of the equations governing the system dynamics.Comment: 4 pages, 5 figure

Preliminary Results on Masquerader Detection using Compression Based Similarity Metrics

This paper extends a series of experiments performed by Schonlau et al. [1] on the detection of computer masqueraders (i.e. illegitimate users trying to impersonate legitimate ones). A compression-based classication algorithm called Normalized Compression Distance or NCD, developed by Vitányi et al. [2] is applied on the same data set. It is shown that the NCD-based approach performs as well as the methods previously tried by Schonlau et al. Future work, possible enhancements and directions of further research on this topic are presented as well.Sociedad Argentina de Informática e Investigación Operativ

User clustering based on keystroke dynamics

The PAM clustering algorithm is applied on the Si6 keystroke dataset in order to identify sessions of the same users. A number of heuristical outlier lters based on statistical properties of keystroke latencies are proposed and run on the dataset. Di erent tests are performed varying the number of digraphs that compose each observation and its dimensionality, in order to verify the assumption that more data gives a better quality of clustering and to estimate the minimum required number of dimensions. The number of clusters is estimated through the silhouette algorithm. Resulting clustering accuracy is measured by means of the F-measure, showing the viability of user identi cation through keystroke analysis.Presentado en el V Workshop Arquitectura, Redes y Sistemas Operativos (WARSO)Red de Universidades con Carreras en Informática (RedUNCI

Preliminary Results on Masquerader Detection using Compression Based Similarity Metrics

This paper extends a series of experiments performed by Schonlau et al. [1] on the detection of computer masqueraders (i.e. illegitimate users trying to impersonate legitimate ones). A compression-based classication algorithm called Normalized Compression Distance or NCD, developed by Vitányi et al. [2] is applied on the same data set. It is shown that the NCD-based approach performs as well as the methods previously tried by Schonlau et al. Future work, possible enhancements and directions of further research on this topic are presented as well.Sociedad Argentina de Informática e Investigación Operativ

User clustering based on keystroke dynamics

The PAM clustering algorithm is applied on the Si6 keystroke dataset in order to identify sessions of the same users. A number of heuristical outlier lters based on statistical properties of keystroke latencies are proposed and run on the dataset. Di erent tests are performed varying the number of digraphs that compose each observation and its dimensionality, in order to verify the assumption that more data gives a better quality of clustering and to estimate the minimum required number of dimensions. The number of clusters is estimated through the silhouette algorithm. Resulting clustering accuracy is measured by means of the F-measure, showing the viability of user identi cation through keystroke analysis.Presentado en el V Workshop Arquitectura, Redes y Sistemas Operativos (WARSO)Red de Universidades con Carreras en Informática (RedUNCI