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Title of the Paper: An Improved Nested
Partitions Algorithm Based on Simulated Annealing in Complex Decision
Problem Optimization
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Authors: Chang-Rui Yu and Yan Luo
Abstract: This
paper introduces the main ideas of the nested partitions (NP) method,
analyses its efficiency theoretically and proposes the way to improve the
optimization efficiency of the algorithm. Then the paper introduces the
simulated annealing (SA) algorithm and incorporates the ideas of SA into two
of the arithmetic operators of NP algorithm to form the combined NP/SA
algorithm. Moreover, the paper presents the explicit optimization procedure
of the combined algorithm NP/SA and explains the feasibility and superiority
of it. The NP/SA algorithm adopts the global optimization ability of NP
algorithm and the local search ability of SA algorithm so that it improves
the optimization efficiency and the convergence rate. This paper also
illustrates the NP/SA algorithm through an optimization example.
Keywords: Nested partitions algorithm, Simulated annealing, Complex decision
problem.
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Questions, Discussion ...
Title of the Paper:
Faulty-Tolerant Algorithm for Mapping a Complete
Binary Tree in an IEH
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Authors: Shih-Jung Wu, Jen-Chih
Lin, and Huan-Chao Keh
Abstract: Different parallel architectures may require different algorithms
to make the existent algorithms on one architecture be easily transformed to
or implemented on another architecture. This paper proposes a novel
algorithm for embedding complete binary trees in a faulty Incrementally
Extensible Hypercube (IEH). Furthermore, to obtain the replaceable node of
the faulty node, 2-expansion is permitted such that up to (n+1) faults can
be tolerated with dilation 3, congestion 1 and load 1. The presented
embedding methods are optimized mainly for balancing the processor loads,
while minimizing dilation and congestion as far as possible. According to
the result, we can map the parallel algorithms developed by the structure of
complete binary tree in an IEH. These methods of reconfiguring enable
extremely high-speed parallel computation.
Keywords:
Hypercube, Incrementally Extensible Hypercube, Complete binary tree,
Fault-Tolerance, Embedding
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Title of the Paper: Height, Size Performance of
Complete and Nearly Complete Binary Search Trees in Dictionary Applications
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Authors: Ahmed Tarek
Abstract: Trees are frequently used data structures for fast access to the
stored data. Data structures like arrays, vectors and linked lists are
limited by the trade-off between the ability to perform a fast search and
the ability to resize easily. Binary Search Trees are an alternative data
structure that is both dynamic in size and easily searchable. Now-a-days,
more and more people are getting interested in using electronic organizers
and telephone dictionaries avoiding the hard copy counter parts. In this
paper, performance of complete and nearly complete binary search trees are
analyzed in terms of the number of tree nodes and the tree heights.
Analytical results are used together with an electronic telephone dictionary
for a medium sized organization. It’s performance is evaluated in lieu of
the real-world applications. The concept of multiple keys in data structure
literature is relatively new, and was first introduced by the author. To
determine the dictionary performance, another algorithm for determining the
internal and the external path lengths is also discussed. New results on
performance analysis are presented. Using tree-sort, individual records
inside the dictionary may be displayed in ascending order.
Keywords: Complete Binary Search Tree, Nearly Complete Binary Search Tree,
Electronic Telephone Dictionary, Performance Analysis, Performance Measurement,
Logarithmic Time Complexity.
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Title of the Paper: Case-Oriented Alert Correlation
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Authors: Jidong Long and Daniel G. Schwartz
Abstract: Correlating alerts is of importance for identifying complex attacks and discarding false alerts.
Most popular alert correlation approaches employ some well-de ned knowledge to uncover the connections
among alerts. However, acquiring, representing and justifying such knowledge has turned out to
be a nontrivial task. In this paper, we propose a novel method to work around these diculties by using
case-based reasoning (CBR). In our application, a case, constructed from training data, serves as an
example of correlated alerts. It consists of a pattern of alerts caused by an attack and the identity of the
attack. The runtime alert stream is then compared with each case, to see if any subset of the runtime
alerts are similar to the pattern in the case. The process is reduced to a matching problem. Two kinds
of matching methods were explored. The latter is much more ecient than the former. Our experiments
with the DARPA Grand Challenge Problem attack simulator have shown that both produce almost the
same results and that case-oriented alert correlation is e
ective in detecting intrusions
Keywords: Alert Correlation, Case-Based Reasoning, Data Mining, Intrusion Detection
Title of the Paper: CORAL - Online Monitoring in Distributed
Applications: Issues and Solutions
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Authors: Ivan Zoraja, Ivan Zulim, and Maja Štula
Abstract: In this paper we describe and evaluate issues that come up in the development of online monitoring systems which connect software tools to a running distributed application. Our primary intension was to elaborate how to deal with complex middleware mechanisms that cater for the middleware functionality in a way transparent to the users and tools. Our current implementation, called Coral, manages DSM mechanisms that provide an abstraction of shared memory on loosely coupled hardware, and allows multiple tools to perform consistent yet efficient operations on the entities being monitored. Since our primary design choice with Coral was portability we will port Coral to distributed environments based on the SOA technology.
Keywords: Online Monitoring, DSM, Tools, Process migration, Performance analysis, Checkpointing
Title of the Paper: Mining Strong Positive and Negative Sequential Patterns
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Authors: Nancy P. Lin, Hung-Jen Chen, Wei-Hua Hao,
Hao-En Chueh, Chung-I Chang
Abstract: In data mining field, sequential pattern mining can be applied in divers applications such as basket analysis, web access patterns analysis, and quality control in manufactory engineering, etc. Many methods have been proposed for mining sequential patterns. However, conventional methods only consider the occurrences of itemsets in customer sequences. The sequential patterns discovered by these methods are called as positive sequential patterns, i.e., such sequential patterns only represent the occurrences of itemsets. In practice, the absence of a frequent itemset in a sequence may imply significant information. We call a sequential pattern as negative sequential pattern, which also represents the absence of itemsets in a sequence. The two major difficulties in mining sequential patterns, especially negative ones, are that there may be huge number of candidates generated, and most of them are meaningless. In this paper, we proposed a method for mining strong positive and negative sequential patterns, called PNSPM. In our method, the absences of itemsets are also considered. Besides, only sequences with high degree of interestingness will be selected as strong sequential patterns. An example was taken to illustrate the process of PNSPM. The result showed that PNSPM could prune a lot of redundant candidates, and could extract meaningful sequential patterns from a large number of frequent sequences.
Keywords: Data mining, Itemset, Frequent sequence, Positive sequential pattern, Negative sequential pattern, Strong sequential pattern
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