**Seminar on
Applied Mathematics**

**PROGRAM**

Matematički fakultet

Fakultet organizacionih nauka

JUPIM

MI SANU, Knez Mihailova 36, sala 305

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Sreda, 01.07.2009. u 14:15, Sala 128, SF BG:
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Vir V. Phoha, Louisiana Tech University, SAD
Dynamic Fusion for Rare Event Detection in Computer Networks
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Abstract. The talk consists of two parts: the first part gives a brief
overview of the
Center for Secure Cyberspace (CSC), its. infrastructure support for
research, and a brief overview of some ongoing research projects. The
second part consists of a description of a cascading algorithm for detecting
rare events that fuses decisions dynamically. An abstract of the dynamic
cascading algorithm follows.
Fusion of multiple classifier systems can result in enhanced accuracy and
performance. Traditional classifiers generally do not work well with data
spaces having class skew, that is instances of one class overwhelm the
instance of another class. To overcome the class skew problem for detection
of rare events, we present .K-Means+ID3,. a method to cascade k-Means
clustering and the ID3 decision tree learning methods for classifying
anomalous and normal activities in a computer network systems. The k-Means
clustering method first partitions the training instances into k clusters
using Euclidean distance similarity. On each cluster, representing a density
region of normal or anomaly instances, we build an ID3 decision tree. The
decision tree on each cluster refines the decision boundaries by learning
the subgroups within the cluster. To obtain a final decision on
classification, the decisions of the k-Means and ID3 methods are combined
using two rules: 1) the Nearest-neighbor rule and 2) the Nearestconsensus
rule. Results show that the detection accuracy of the K-Means+ID3 method is
as high as 96.24 percent at a false-positive-rate of 0.03 percent on network
anomaly data.
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Cetvrtak, 02.07.2009. u 14:15, SALA 2, SANU:
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Zoran Obradovic, Temple University i MI SANU
Sequence Alignment and Structural Disorder:
A Substitution Matrix for an Extended Alphabet
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Abstract. In protein sequence alignment algorithms, a substitution matrix of
20x20 alignment parameters is used to describe the rates of amino acid
substitutions over time. Development and evaluation of most substitution
matrices including the BLOSUM family was based almost entirely on fully
structured proteins. Structurally disordered proteins (i.e. proteins that
lack structure, either in part or as a whole) that have been shown to be
very common in nature have a significantly different amino acid composition
than ordered (i.e. structured) proteins. Furthermore, the sequence evolution
rate is higher in unstructured as compared to structured regions of proteins
containing both structured and unstructured regions. These results cast
doubt on appropriateness of the BLOSUM substitution matrices for alignment
of structurally disordered proteins. To address this problem, we take into
the account the concept of structural disorder by extending the alphabet for
sequence representation to 2x20=40 symbols, 20 for amino acids in disordered
regions and 20 for amino acids in ordered regions. A 40x40 substitution
matrix is required for alignment of sequences represented in the extended
alphabet. Such an expanded matrix contains 20x20 submatrices that correspond
to matching ordered-ordered, ordered-disordered, and disordered-disordered
pairs of residues. In this talk we will describe an iterative procedure that
we used to estimate such a 40x40 substitution matrix. The iterative
procedure converged with stable results with respect to the choice of the
sequences in the dataset. In the obtained 40x40 matrix we found substantial
differences between the 20x20 submatrices corresponding to ordered-ordered,
ordered-disordered, and disordered-disordered region matching. These
differences provide evidence that for alignment of protein sequences that
contain disordered segments, the discovered substitution matrix is more
appropriate than the BLOSUM substitution matrices. At the same time, the new
substitution matrix is applicable for sequence alignment of fully ordered
proteins as its order-order submatrix is very similar to a BLOSUM matrix.
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RUKOVODIOCI SEMINARA
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Vera Kovačević-Vujčić
Milan Dražić
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