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Speed
up of Reindexing in Adaptive Particle Swarm Optimization
Niraimathi Ponnusamy and Bhoopathy Krishnaswamy
Department of Electronics Engineering, Anna University,
India
Abstract: Palette
re-ordering is a class of pre-processing method with the objective to
manipulate the palette index such that the adjacent symbols are assigned close
indices in the symbol space, thus enhancing the compressibility of the image
with many lossless compressors. Finding an exact reordered palette would
certainly be exhaustive and computationally complex. A solution to this NP hard
problem is presented by using an Adaptive Particle Swarm Optimization (APSO) to
achieve fast global convergence by maximizing the co-occurrences. A new
algorithm with improved inertia factor is presented here to accelerate the
convergence speed of the reindexing scheme. In this algorithm, the key
parameter inertia weight is formulated as a factor of gradient based rate of particle
convergence. Experimental results assert that the proposed modification helps
in improving APSO performance in terms of solution quality and convergence to
global optima.
Key
words: Reindexing, palette-indexed image, Cross Entropy (CE), rate of
particle convergence (k), improved Inertia Weight Adaptive Particle Swarm
Optimization (IWAPSO).
Received April 3, 2013; accepted November10,
2014
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Two Layer Defending
Mechanism against DDoS Attacks
Kiruthika
Subramain, Preetha Gunasekaran, and Mercy Selvaraj
Department of Computer Science and Engineering,
Thiagarajar College of Engineering,
Affiliated to Anna University, India
Abstract: Distributed Denial of Service (DDoS)
attackers make a service unavailable for intended users. Attackers use IP
spoofing as a weapon to disguise their identity. The spoofed traffic follows
the same principles as normal traffic, so detection and filtering is very essential. Hop-Count Filtering (HCF) scheme identifies
packet whose source IP address is spoofed. The
information about a
source IP address
and its corresponding
hops from a
server (victim) recorded in a table at the victim. The incoming packet
is checked against this table for authenticity. The design of IP2HC table
reduces the amount of storage space by IP address clustering. The proposed work
filters majority of the spoofed traffic by HCF-SVM algorithm on the network
layer. DDoS attackers using genuine IP
is subjected to traffic limit at the Application layer. The two layer defense approach
protects legitimate traffic from being denied, thereby mitigating DDoS
effectively. HCF - SVM model yields 98.99% accuracy with reduced false positive
rate and the rate limiter punishes the aggressive flows and provides sufficient
bandwidth for legitimate users without any denial of service. The
implementation of the proposed work is carried out on an experimental testbed.
Keywords: DDoS, hop-count, IP2HC table, clustering, IP spoofing, testbed.
Received
November 9, 2012; acceped April 29, 2013
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An Improved Iterative
Segmentation Algorithm using Canny Edge Detector for Skin Lesion Border Detection
J.H.Jaseema Yasmin1and
M.Mohamed Sathik2
1Associate Professor, National College of Engineering,
India
2Principal,
Sadakathullah Appa College, India
Abstract: One of the difficult problems recognized
in image processing and pattern analysis, in particular in medical imaging
applications is Boundary detection. The detection of skin lesion
boundaries accurately allows,
skin cancer detection .There is no
unified approach to this problem, which
has been found to be application
dependent. Early diagnosis of melanoma is a challenge, especially for
general practitioners, as melanomas are hard to distinguish from common moles,
even for experienced dermatologists. Melanoma can be cured by simple excision,
when diagnosed at an early stage. Our proposed improved iterative segmentation
algorithm, using canny edge detector, which is a simple and effective method to
find the border of real skin lesions is presented, that helps in early
detection of malignant melanoma and its performance is compared with the
segmentation algorithm using canny detector[16], developed by us previously for
border detection of real skin lesions. The experimental results demonstrate the
successful border detection of noisy real skin lesions by our proposed improved
iterative segmentation algorithm using canny detector. We conclude that our
proposed segmentation algorithm,
segments the lesion from the image even in the presence of noise for a variety
of lesions, and skin types and its performance is more reliable than the
segmentation algorithm[16] that we have developed previously that uses canny
detector, for border detection of real skin lesions for noisy skin lesion
diagnosis.
Keywords: Melanoma, canny edge detector, border
detection, segmentation, skin lesion
Received April 15, 2012; accept February 13, 2013
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VLSI Implementations of
Compressive Image Acquisition Using Block Based Compression Algorithm
Muthukumaran N and Ravi Ramraj
Francis Xavier
Engineering College, Tirunelveli-627003, India.
Abstract: In this research paper consists of
compressing the images within each pixel before the storage processes, hence
the size of the memory gets reduced. This can be done by the proposed method
namely block based compression algorithm which uses the differential coding
scheme. Here differential values are captured and then quantized. The
differential coding scheme uses the concept of selecting the brightest pixel as
the reference pixel. The difference between brightest pixel and subsequent
pixel is calculated and quantized. Hence, their range is compressed and the spatial
redundancy can be removed using block based compression algorithm. Thus, the
proposed scheme reduces the accumulation of error and also reduces the
requirement of memory. Thus, the Peak Signal to Noise Ratio (PSNR) value can be
improved and Bits Per Pixel (BPP) value can be reduced. The future scope of the
project is that the quality of the image can be further improved with high peak
signal to noise ratio value using some other compression techniques.
Key
words: Image capture,
image store, image compression, JPEG, PSNR, compression ratio, CMOS image
sensor, VLSI implementation.
Received May 28, 2013; accepted September 26, 2013
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Vulnerability Analysis of Two
Ultralightweight RFID Authentication Protocols
Yousof Farzaneh1, Mahdi Azizi2, Masoud
Dehkordi1, and Abdolrasoul Mirghadri2
1School of Mathematics, Iran University
of Science and Technology, Iran
2Faculty
of Communication and Information Technology, IHU University, Iran
Abstract: Ultralightweight Radio Frequency Identification (RFID)
authentication protocols are suitable for low-cost RFID tags with restricted
computational power and memory space. Recently, Lee proposed two ultra
lightweight authentication protocols for low-cost RFID tags, namely DIDRFID and
SIDRFID protocols. The first protocol is based on dynamic identity and the
second one on static identity. Lee claimed that his protocols can resist
tracking, replay, impersonation, and DOS attacks. In this paper, we show that Lee’s protocols
are not secure and they are vulnerable against tracking, impersonation, and
full disclosure attacks. Specially, an adversary can accomplish an effective
full disclosure attack on DIDRFID protocol by eavesdropping two consecutive sessions
and gets all the secret information stored on a tag. Also, we demonstrate that
an adversary with ability of obtaining secret information of a single
compromised tag in SIDRFID protocol, can get the secret information of other
tags and she/he can completely control the whole RFID system.
Keywords: Low-cost RFID, cryptography, protocol, vulnerability.
Received
August 8, 2012; accepted July 28, 2013
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Efficient Multimodal Biometric Database
Construction and Protection Schemes
Kebbeb Asma1, Mostefai Messaoud1,
Benmerzoug Fateh1, and Youssef Chahir2
1MSE Laboratory, University of Bordj Bou
Arreridj, Algeria
2GREYC Laboratory, University of Caen, France
Abstract: This work proposes an efficient approach for the construction
and the protection of a dynamic and evolutionary multimodal biometric database.
The last is dedicated to a biometric authentication system operating on a set
of connected sites. For a better protection of acquired data, a topological
watermarking module is developed to dissimulate the related enrolled person’s
files links.
Keywords: Biometric databases,
multimodal authentication, digital watermarking, cross-section
topology.
Received
November 30, 2012; accepted February 21, 2013
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Pairwise Sequence Alignment using Bio-Database
Compression by Improved Fine Tuned Enhanced Suffix Array
Kunthavai A1, Vasantharathna S2,
and Thirumurugan S3
1,3Department of Computer Science & Engineering / IT, Coimbatore
Institute of Technology, India.
2Department of Electrical & Electronics Engineering, Coimbatore
Institute of Technology, India.
Abstract: Sequence alignment is a bioinformatics application
that determines the degree of similarity between nucleotide sequences which is
assumed to have same ancestral relationships. This sequence alignment method
reads query sequence from the user and makes an alignment against large and
genomic sequence data sets and locate targets that are similar to an input
query sequence. Existing accurate algorithm, such as Smith-Waterman and FASTA
are computationally very expensive, which limits their use in practice. The existing search tools, such as BLAST and WU-BLAST, employ heuristics to improve the
speed of such searches. However, such heuristics can sometimes miss targets, in
which many cases are undesirable. Considering the rapid growth of database sizes, this
problem demands ever-growing computation resources,
and remains as a computational challenge. Most common sequence alignment
algorithms like BLAST, WU-BLAST, and SCT searches a given query sequence
against set of database sequences. In
this paper BioDBMPHF Tool has been developed to find pair wise local sequence
alignment by preprocessing the database. Preprocessing is done by means of
finding Longest Common Substring (LCS) from the database of sequences that have
the highest local similarity with a given query sequence and reduces the size
of the database based on frequent common subsequence. In this BioDBMPHF Tool
fine-tuned enhanced suffix array is constructed and used to find LCS.
Experimental results show that HashIndexalgorithm reduces the time and space
complexity to access LCS. Time complexity to find LCS of the HashIndexalgorithm
is O (2 + γ) where ‘γ’ is the time taken to access the pattern. Space
complexity of fine-tuned enhanced suffix array is 5n bytes per character for
reduced enhanced Lcp table and to store bucket table it requires 32 bytes. Data
mining technique is used to cross validate the result. It is proved that the developed
BioDBMPHF Tool effectively compresses the database and obtains same results
compared to that traditional algorithm in approximately half the time taken by
them thereby reducing the time complexity.
Recevied October 25, 2012; accepted January 1, 2013
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Mining
Closed and Multi-Supports-Based
Sequential Pattern in High-Dimensional Dataset
Meng Han1,2,
Zhihai Wang1,and Jidong Yuan1
1School
of Computer and Information Technology,
Beijing Jiaotong University, China
2School
of Computer Science and Engineering,
Beifang University of Nationalities, China
Abstract: Previous mining algorithms on high dimensional datasets, such as
biological dataset, create very large patterns sets as a result which includes small
and discontinuous sequential patterns. These patterns do not bear any useful
information for usage. Mining sequential patterns in such sequences need to
consider different forms of patterns, such as contiguous patterns, local patterns
which appear more than one time in a special sequence and so on. Mining closed
pattern leads to a more compact result set but also a better efficiency. In this
paper, a novel algorithm based on BI - directional extension and multi-supports is
provided specifically for mining contiguous closed patterns in high
dimensional dataset. Three kinds of contiguous
closed sequential patterns are mined which are sequential patterns, local
sequential patterns and total sequential patterns. Thorough performances on
biological sequences have demonstrated that the proposed algorithm reduces
memory consumption and generates compact patterns.
A
detailed analysis of the multi-supports-based results is provided in this
paper.
Keywords: High - dimensional dataset, closed pattern, contiguous pattern, multi - supports,
biological sequences.
Receivsed Junuary 11, 2012; accepted April 29, 2013
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Solving QBF with Heuristic
Small-world Optimization Search Algorithm
Tao Li1 and Nanfeng Xiao2
1Modern Education and Technology Center, South China
Agricultural University, China
2School of Computer
Science and Engineering, South China University of Technology, China
Abstract: In this paper, we
use Gaifman graph to describe the topological structure of the Quantified Boolean
Formulae (QBF), we mainly study the formula family with the small-world network
topology. We analyze the traditional Putnam, Logemann and Loveland (DPLL)
solving algorithm for QBF, then we improve the DPLL algorithm and propose the
solving algorithm framework based on small world optimization search algorithm,
we apply this small world optimization search algorithm to determine the order
of the DPLL branch variable. Our result proves that small world optimization
search algorithm has a certain degree of effectiveness to improve the solving
efficiency. It is valuable as an incomplete solution algorithm for search-based
solver.
Keywords: QBF, small-world,
search algorithm, optimization algorithm.
Received July 26,
2012; accepted February 11, 2013
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Balanced Workload Clusters for Distributed
Object Oriented Software
Hebat-Allah M. Ragab1,
Amany Sarhan1, Al Sayed A. H. Sallam1, Reda A. AMMAR2
1 Computer and Control
Engineering Department, Faculty of Engineering, Tanta University, Egypt
2 Computer Science and
Engineering Department, School of Engineering, University of Connecticut, USA
Abstract: When clustering objects to be allocated on a number of nodes, most
researches focus only on either the communication cost between clusters or the
balancing of the workload on the nodes. Load balancing is a technique to
distribute workload evenly across two or more
computers, network links, CPUs, hard drives, or other resources, in
order to get optimal resource utilization, maximize throughput, minimize
response time, and avoid overload. In this paper, we introduce three clustering
algorithms that obtain balanced clusters for homogeneous clustered with
minimized communication cost.
Keywords: Load balance; Distributed system; Software Restructuring; Cluster
Algorithms.
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An Accelerometer-Based Approach to Evaluate 3D
Unistroke Gestures
Tahir Madani1,2,*, Muhammad Tahir3, Sheikh Ziauddin1, Syed Raza1, Mirza Ahmed1,
Majid Khan1, and Mahmood
Ashraf 4,5
1Department of Computer
Science, COMSATS Institute of Information Technology, Pakistan
2Department of Information
Technology, University Technology Petronas, Malaysian
3Faculty of Computing and
Information Technology, King Abdulaziz University, Kingdom of Saudi Arabia
4Department of Computer Science,
Science and Technology, Pakistan
5Department of Software
Engineering, Universiti Teknologi, Malaysia
Abstract: This paper presents an evaluation of Three Dimensional (3D) unistroke
human arm gestures. Our scheme employs an accelerometer-based approach by using
Nintendo™ Wiimote as a gesture device. The system takes acceleration signals
from Wiimote in order to classify different gestures. It deals with numeric
gestures, i.e., digits from 0 to 9 and simple mathematical operator gestures
for addition, subtraction, multiplication and division. Two techniques, Dynamic
Time Warping (DTW) and 2D trajectories are used to recognize and classify
gestures. Successful recognition rates indicate that performing 3D gestures
using accelerometer-based devices is intuitive and provides an effective means
of interaction with computers.
Keywords: Human computer interaction, 3D gestures, accelerometer, 3D calculator,
dynamic time warping, 2D trajectories, wiimote.
Received May 29, 2012; accepted September 26, 2013
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An Artificial Neural Network
Approach for Sentence Boundary Disambiguation in Urdu Language Text
Shazia
Raj, Zobia Rehman, Sonia Rauf, Rehana Siddique, and Waqas Anwar
Department
of Computer Science, COMSATS Institute of Information Technology, Pakistan
Abstract: Sentence boundary
identification is an important step for text processing tasks, e.g., machine
translation, POS tagging, text summarization etc., in this paper we present an
approach comprising of feed forward neural network along with part of speech
information of the words in a corpus. Proposed adaptive system has been tested
after training it with varying sizes of data and threshold values. The best
results, our system produced are 93.05% precision, 99.53% recall and 96.18%
f-measure.
Keywords: Sentence boundary
identification, feed forwardneural network, back propagation learning
algorithm.
Received April
22, 2013; accepted September 19, 2013
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Distinguishing Attack on CSA
Kai Zhang and Jie Guan
Zhengzhou
Information Science and Technology Institute, China
Abstract: Common
Scrambling Algorithm (CSA) has been used to encrypt European cable digital television signals
since 1994. Although the key size of CSA is small, up to now, there haven’t any
effective crypto results which can break the algorithm totally. Based on the
idea of slide resynchronization attack, a distinguishing attack which can
distinguish the keystream of the stream cipher from a purely random sequence
with computational complexity of O (215) is proposed. According to
the distinguishing attack, the 64 bit initial key can be recovered with
computational complexity of O (255).
Keywords: DVB-CSA, distinguishing attack, slide resynchronization attack, hybrid cipher.
Received August 31, 2012; accepted February 23, 2014
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