An Intrusion Detection System (IDS) is a program that analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. An IDS does not eliminate the use of preventive mechanism but it works as the last defensive mechanism in securing the system. This paper evaluates the performances of Estimation of Distribution Algorithm (EDA) to train...

An Intrusion Detection System (IDS) is a program that analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. An IDS does not eliminate the use of preventive mechanism but it works as the last defensive mechanism in securing the system. This Chapter evaluates the performances of two Genetic Programming techniques for IDS namely...

In this paper we show that the Random Forest (RF) approach can be successfully implemented for language modeling of an inflectional language for Automatic Speech Recognition (ASR) tasks. While Decision Trees (DTs) perform worse than a conventional trigram language model (LM), RFs outperform the latter. WER (up to 3.4% relative) and perplexity (10%) reduction over the trigram model can be gained...

Genomic selection (GS) emphasizes the simultaneous prediction of genetic effects thousands scattered markers over genome. Several statistical methodologies have been used in GS for merit. In general, such require certain assumptions about data, as normality distribution phenotypic values. To circumvent non-normality values, literature suggests use Bayesian Generalized Linear Regression (GBLASSO...

Abstract In this work, the concept of an Artificial Intelligence-based (AI) Digital Twin (DT) aircraft system is introduced, with goal to improve corresponding MRO Operations. More specifically, current study aims obtaining knowledge on optimal placement sensors in ideal Power Electronics Cooling System (PECS) a modern airliner, aiming input data as basis for AI-based DT. The three main fluid p...

Road networks are one of the main urban features. Therefore, road parts extraction from high-resolution remotely sensed imagery and updated database beneficial for many GIS applications. However, owing to presence various types obstacles in images, such as shadows, cars, trees, with similar transparency spectral values class, achieving accurate using different classification segmentation method...

The aim of bankruptcy prediction in the areas of data mining and machine learning is to develop an effective model which can provide the higher prediction accuracy. In the prior literature, various classification techniques have been developed and studied, in/with which classifier ensembles by combining multiple classifiers approach have shown their outperformance over many single classifiers. ...

A priori selection of models for use in phylogeny estimation from molecular sequence data is increasingly important as the number and complexity of available models increases. The Bayesian information criterion (BIC) and the derivative decision-theoretic (DT) approaches rely on a conservative approximation to estimate the posterior probability of a given model. Here, we extended the DT method b...

We explore the possibility of learning user competence from a text by using natural language processing and machine learning (ML) methods. In our context, competence is defined as the ability to identify the wildlife appearing in images and classifying into species correctly. We evaluate and compare the performance (regarding accuracy and Fmeasure) of the three ML methods, Naive Bayes (NB), Dec...