Abstract: Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.
Abstract: Classification of Persian printed numeral characters
has been considered and a proposed system has been introduced. In
representation stage, for the first time in Persian optical character
recognition, extended moment invariants has been utilized as
characters image descriptor. In classification stage, four different
classifiers namely minimum mean distance, nearest neighbor rule,
multi layer perceptron, and fuzzy min-max neural network has been
used, which first and second are traditional nonparametric statistical
classifier. Third is a well-known neural network and forth is a kind of
fuzzy neural network that is based on utilizing hyperbox fuzzy sets.
Set of different experiments has been done and variety of results has
been presented. The results showed that extended moment invariants
are qualified as features to classify Persian printed numeral
characters.
Abstract: Persian (Farsi) script is totally cursive and each character is written in several different forms depending on its former and later characters in the word. These complexities make automatic handwriting recognition of Persian a very hard problem and there are few contributions trying to work it out. This paper presents a novel practical approach to online recognition of Persian handwriting which is based on representation of inputs and patterns with very simple visual features and comparison of these simple terms. This recognition approach is tested over a set of Persian words and the results have been quite acceptable when the possible words where unknown and they were almost all correct in cases that the words where chosen from a prespecified list.
Abstract: Analysis and visualization of microarraydata is veryassistantfor biologists and clinicians in the field of diagnosis and treatment of patients. It allows Clinicians to better understand the structure of microarray and facilitates understanding gene expression in cells. However, microarray dataset is a complex data set and has thousands of features and a very small number of observations. This very high dimensional data set often contains some noise, non-useful information and a small number of relevant features for disease or genotype. This paper proposes a non-linear dimensionality reduction algorithm Local Principal Component (LPC) which aims to maps high dimensional data to a lower dimensional space. The reduced data represents the most important variables underlying the original data. Experimental results and comparisons are presented to show the quality of the proposed algorithm. Moreover, experiments also show how this algorithm reduces high dimensional data whilst preserving the neighbourhoods of the points in the low dimensional space as in the high dimensional space.
Abstract: WiMAX is defined as Worldwide Interoperability for
Microwave Access by the WiMAX Forum, formed in June 2001 to
promote conformance and interoperability of the IEEE 802.16
standard, officially known as WirelessMAN. The attractive features
of WiMAX technology are very high throughput and Broadband
Wireless Access over a long distance. A detailed simulation
environment is demonstrated with the UGS, nrtPS and ertPS service
classes for throughput, delay and packet delivery ratio for a mixed
environment of fixed and mobile WiMAX. A simple mobility aspect
is considered for the mobile WiMAX and the PMP mode of
transmission is considered in TDD mode. The Network Simulator 2
(NS-2) is the tool which is used to simulate the WiMAX network
scenario. A simple Priority Scheduler and Weighted Round Robin
Schedulers are the WiMAX schedulers used in the research work
Abstract: In this paper we propose a method for recognition of
adult video based on support vector machine (SVM). Different kernel
features are proposed to classify adult videos. SVM has an advantage
that it is insensitive to the relative number of training example in
positive (adult video) and negative (non adult video) classes. This
advantage is illustrated by comparing performance between different
SVM kernels for the identification of adult video.
Abstract: One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.
Abstract: The approach based on the wavelet transform has
been widely used for image denoising due to its multi-resolution
nature, its ability to produce high levels of noise reduction and the
low level of distortion introduced. However, by removing noise, high
frequency components belonging to edges are also removed, which
leads to blurring the signal features. This paper proposes a new
method of image noise reduction based on local variance and edge
analysis. The analysis is performed by dividing an image into 32 x 32
pixel blocks, and transforming the data into wavelet domain. Fast
lifting wavelet spatial-frequency decomposition and reconstruction is
developed with the advantages of being computationally efficient and
boundary effects minimized. The adaptive thresholding by local
variance estimation and edge strength measurement can effectively
reduce image noise while preserve the features of the original image
corresponding to the boundaries of the objects. Experimental results
demonstrate that the method performs well for images contaminated
by natural and artificial noise, and is suitable to be adapted for
different class of images and type of noises. The proposed algorithm
provides a potential solution with parallel computation for real time
or embedded system application.
Abstract: Classification is an interesting problem in functional
data analysis (FDA), because many science and application problems
end up with classification problems, such as recognition, prediction,
control, decision making, management, etc. As the high dimension
and high correlation in functional data (FD), it is a key problem to
extract features from FD whereas keeping its global characters, which
relates to the classification efficiency and precision to heavens. In this
paper, a novel automatic method which combined Genetic Algorithm
(GA) and classification algorithm to extract classification features is
proposed. In this method, the optimal features and classification model
are approached via evolutional study step by step. It is proved by
theory analysis and experiment test that this method has advantages in
improving classification efficiency, precision and robustness whereas
using less features and the dimension of extracted classification
features can be controlled.
Abstract: Water Sensitive Urban Design (WSUD) features are
increasingly used to treat and manage polluted stormwater runoff in urbanised areas. It is important to monitor and evaluate the effectiveness of the infrastructure in achieving their intended performance targets after constructing and operating these features
overtime. The paper presents the various methods of analysis used to
assess the effectiveness of the in-situ WSUD features, such as: onsite visual inspections during operational and non operational periods, maintenance audits and periodic water quality testing. The results will contribute to a better understanding of the operational and
maintenance needs of in-situ WSUD features and assist in providing recommendations to better manage life cycle performance.
Abstract: This paper explores the features of political economy in the dynamics of representative politics in India. Politics is seen as enhancing economic benefits through acquiring and maintenance of power in the realm of democratic set up. The system of representation is riddled with competitive populism. Emerging leaders and parties are forced to accommodate their ideologies in coping with competitive politics. Electoral politics and voting behaviour reflect series of influences mooted by the politicians. Voters are accustomed to expect benefits outs of state exchequer. The electoral competitors show a changing phase of investment and return policy. Every elector has to spend and realize his costs in his tenure. In the case of defeated electors, even the cost recovery is not possible directly; there are indirect means to recover their costs. The series of case studies show the method of party funding, campaign financing, electoral expenditure, and cost recovery. Regulations could not restrict the level of spending. Several cases of disproportionate accumulation of wealth by the politicians reveal that money played a major part in electoral process. The political economy of representative politics hitherto ignores how a politician spends and recovers his cost and multiples his wealth. To be sure, the acquiring and maintenance of power is to enhance the wealth of the electors.
Abstract: An application framework provides a reusable
design and implementation for a family of software systems.
Frameworks are introduced to reduce the cost of a product line
(i.e., family of products that share the common features). Software
testing is a time consuming and costly ongoing activity during the
application software development process. Generating reusable test
cases for the framework applications at the framework
development stage, and providing and using the test cases to test
part of the framework application whenever the framework is used
reduces the application development time and cost considerably.
Framework Interface Classes (FICs) are classes introduced by
the framework hooks to be implemented at the application
development stage. They can have reusable test cases generated at
the framework development stage and provided with the
framework to test the implementations of the FICs at the
application development stage. In this paper, we conduct a case
study using thirteen applications developed using three
frameworks; one domain oriented and two application oriented.
The results show that, in general, the percentage of the number of
FICs in the applications developed using domain frameworks is, on
average, greater than the percentage of the number of FICs in the
applications developed using application frameworks.
Consequently, the reduction of the application unit testing time
using the reusable test cases generated for domain frameworks is,
in general, greater than the reduction of the application unit testing
time using the reusable test cases generated for application
frameworks.
Abstract: After Apple's first introduction its smart phone, iPhone
in the end of 2009 in Korea, the number of Korean smarphone users
had been rapidly increasing so that the half of Korean population
became smart phone users as of February, 2012. Currently, smart
phones are positioned as a major digital media with powerful
influences in Korea. And, now, Koreans are leaning new information,
enjoying games and communicating other people every time and
everywhere. As smart phone devices' performances increased, the
number of usable services became more while adequate GUI
developments are required to implement various functions with smart
phones. The strategy to provide similar experiences on smart phones
through familiar features based on employment of existing media's
functions mostly contributed to smart phones' popularization in
connection with smart phone devices' iconic GUIs.
The spread of Smart phone increased mobile web accesses.
Therefore, the attempts to implement PC's web in the smart phone's
web are continuously made. The mobile web GUI provides familiar
experiences to users through designs adequately utilizing the smart
phone's GUIs. As the number of users familiarized to smart phones
and mobile web GUIs, opposite to reversed remediation from many
parts of PCs, PCs are starting to adapt smart phone GUIs.
This study defines this phenomenon as the reversed remediation,
and reviews the reversed remediation cases of Smart phone GUI'
characteristics of PCs. For this purpose, the established study issues
are as under:
· what is the reversed remediation?
· what are the smart phone GUI's characteristics?
· what kind of interrelationship exist s between the smart phone and
PC's web site?
It is meaningful in the forecast of the future GUI's change by
understanding of characteristics in the paradigm changes of PC and
smart phone's GUI designs. This also will be helpful to establish
strategies for digital devices' development and design.
Abstract: Due to its special data structure and manipulative principle, Object-Oriented Database (OODB) has a particular security protection and authorization methods. This paper first introduces the features of security mechanism about OODB, and then talked about authorization checking process of OODB. Implicit authorization mechanism is based on the subject hierarchies, object hierarchies and access hierarchies of the security authorization modes, and simplifies the authorization mode. In addition, to combine with other authorization mechanisms, implicit authorization can make protection on the authorization of OODB expediently and effectively.
Abstract: Research has suggested that implicit learning tasks
may rely on episodic processing to generate above chance
performance on the standard classification tasks. The current
research examines the invariant features task (McGeorge and Burton,
1990) and argues that such episodic processing is indeed important.
The results of the experiment suggest that both rejection and
similarity strategies are used by participants in this task to
simultaneously reject unfamiliar items and to accept (falsely) familiar
items. Primarily these decisions are based on the presence of low or
high frequency goal based features of the stimuli presented in the
incidental learning phase. It is proposed that a goal based analysis of
the incidental learning task provides a simple step in understanding
which features of the episodic processing are most important for
explaining the match between incidental, implicit learning and test
performance.
Abstract: The current research paper is an implementation of
Eigen Faces and Karhunen-Loeve Algorithm for face recognition.
The designed program works in a manner where a unique
identification number is given to each face under trial. These faces
are kept in a database from where any particular face can be matched
and found out of the available test faces. The Karhunen –Loeve
Algorithm has been implemented to find out the appropriate right
face (with same features) with respect to given input image as test
data image having unique identification number. The procedure
involves usage of Eigen faces for the recognition of faces.
Abstract: In this paper we present an off line system for the
recognition of the handwritten numeric chains. Our work is divided
in two big parts. The first part is the realization of a recognition
system of the isolated handwritten digits. In this case the study is
based mainly on the evaluation of neural network performances,
trained with the gradient back propagation algorithm. The used
parameters to form the input vector of the neural network are
extracted on the binary images of the digits by several methods: the
distribution sequence, the Barr features and the centred moments of
the different projections and profiles. The second part is the
extension of our system for the reading of the handwritten numeric
chains constituted of a variable number of digits. The vertical
projection is used to segment the numeric chain at isolated digits and
every digit (or segment) will be presented separately to the entry of
the system achieved in the first part (recognition system of the
isolated handwritten digits). The result of the recognition of the
numeric chain will be displayed at the exit of the global system.
Abstract: Intrusion Detection System is significant in network
security. It detects and identifies intrusion behavior or intrusion
attempts in a computer system by monitoring and analyzing the
network packets in real time. In the recent year, intelligent algorithms
applied in the intrusion detection system (IDS) have been an
increasing concern with the rapid growth of the network security.
IDS data deals with a huge amount of data which contains irrelevant
and redundant features causing slow training and testing process,
higher resource consumption as well as poor detection rate. Since the
amount of audit data that an IDS needs to examine is very large even
for a small network, classification by hand is impossible. Hence, the
primary objective of this review is to review the techniques prior to
classification process suit to IDS data.
Abstract: In this paper we present a novel approach for face image coding. The proposed method makes a use of the features of video encoders like motion prediction. At first encoder selects appropriate prototype from the database and warps it according to features of encoding face. Warped prototype is placed as first I frame. Encoding face is placed as second frame as P frame type. Information about features positions, color change, selected prototype and data flow of P frame will be sent to decoder. The condition is both encoder and decoder own the same database of prototypes. We have run experiment with H.264 video encoder and obtained results were compared to results achieved by JPEG and JPEG2000. Obtained results show that our approach is able to achieve 3 times lower bitrate and two times higher PSNR in comparison with JPEG. According to comparison with JPEG2000 the bitrate was very similar, but subjective quality achieved by proposed method is better.
Abstract: The incorporation of renewable energy sources for the sustainable electricity production is undertaking a more prominent role in electric power systems. Thus, it will be an indispensable incident that the characteristics of future power networks, their prospective stability for instance, get influenced by the imposed features of sustainable energy sources. One of the distinctive attributes of the sustainable energy sources is exhibiting the stochastic behavior. This paper investigates the impacts of this stochastic behavior on the small disturbance rotor angle stability in the upcoming electric power networks. Considering the various types of renewable energy sources and the vast variety of system configurations, the sensitivity analysis can be an efficient breakthrough towards generalizing the effects of new energy sources on the concept of stability. In this paper, the definition of small disturbance angle stability for future power systems and the iterative-stochastic way of its analysis are presented. Also, the effects of system parameters on this type of stability are described by performing a sensitivity analysis for an electric power test system.