Displaying similar documents to “Classification Trees as a Technique for Creating Anomaly-Based Intrusion Detection Systems”

KIS: An automated attribute induction method for classification of DNA sequences

Rafał Biedrzycki, Jarosław Arabas (2012)

International Journal of Applied Mathematics and Computer Science

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This paper presents an application of methods from the machine learning domain to solving the task of DNA sequence recognition. We present an algorithm that learns to recognize groups of DNA sequences sharing common features such as sequence functionality. We demonstrate application of the algorithm to find splice sites, i.e., to properly detect donor and acceptor sequences. We compare the results with those of reference methods that have been designed and tuned to detect splice sites....

Comparison of speaker dependent and speaker independent emotion recognition

Jan Rybka, Artur Janicki (2013)

International Journal of Applied Mathematics and Computer Science

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This paper describes a study of emotion recognition based on speech analysis. The introduction to the theory contains a review of emotion inventories used in various studies of emotion recognition as well as the speech corpora applied, methods of speech parametrization, and the most commonly employed classification algorithms. In the current study the EMO-DB speech corpus and three selected classifiers, the k-Nearest Neighbor (k-NN), the Artificial Neural Network (ANN) and Support Vector...

Bringing introspection into BlobSeer: Towards a self-adaptive distributed data management system

Alexandra Carpen-Amarie, Alexandru Costan, Jing Cai, Gabriel Antoniu, Luc Bougé (2011)

International Journal of Applied Mathematics and Computer Science

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Introspection is the prerequisite of autonomic behavior, the first step towards performance improvement and resource usage optimization for large-scale distributed systems. In grid environments, the task of observing the application behavior is assigned to monitoring systems. However, most of them are designed to provide general resource information and do not consider specific information for higher-level services. More precisely, in the context of data-intensive applications, a specific...

Manageable Workflows for Processing Parallel Sequencing Data

Krachunov, Milko, Kulev, Ognyan, Simeonova, Valeriya, Nisheva, Maria, Vassilev, Dimitar (2014)

Serdica Journal of Computing

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ACM Computing Classification System (1998): D.2.11, D.1.3, D.3.1, J.3, C.2.4. Data analysis after parallel sequencing is a process that uses combinations of software tools that is often subject to experimentation and on-the-fly substitution, with the necessary file conversion. This article presents a developing system for creating and managing workflows aiding the tasks one encounters after parallel sequences, particularly in the area of metagenomics. The semantics, description...