Abstract: In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.
Abstract: Scale Invariant Feature Transform (SIFT) has been
widely applied, but extracting SIFT feature is complicated and
time-consuming. In this paper, to meet the demand of the real-time
applications, SIFT is parallelized and optimized on cluster system,
which is named pSIFT. Redundancy storage and communication are
used for boundary data to improve the performance, and before
representation of feature descriptor, data reallocation is adopted to
keep load balance in pSIFT. Experimental results show that pSIFT
achieves good speedup and scalability.
Abstract: In this paper we present a system for classifying videos
by frequency spectra. Many videos contain activities with repeating
movements. Sports videos, home improvement videos, or videos
showing mechanical motion are some example areas. Motion of these
areas usually repeats with a certain main frequency and several side
frequencies. Transforming repeating motion to its frequency domain
via FFT reveals these frequencies. Average amplitudes of frequency
intervals can be seen as features of cyclic motion. Hence determining
these features can help to classify videos with repeating movements.
In this paper we explain how to compute frequency spectra for video
clips and how to use them for classifying. Our approach utilizes series
of image moments as a function. This function again is transformed
into its frequency domain.
Abstract: Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in controlling the non linear system.
Abstract: Demand over web services is in growing with increases number of Web users. Web service is applied by Web application. Web application size is affected by its user-s requirements and interests. Differential in requirements and interests lead to growing of Web application size. The efficient way to save store spaces for more data and information is achieved by implementing algorithms to compress the contents of Web application documents. This paper introduces an algorithm to reduce Web application size based on reduction of the contents of HTML files. It removes unimportant contents regardless of the HTML file size. The removing is not ignored any character that is predicted in the HTML building process.
Abstract: This paper proposes an architectural and graphical
user interface (GUI) design of a traditional Thai musical instrument
application for tablet computers for practicing “Ranaad Ek" which is
a trough-resonated keyboard percussion instrument. The application
provides percussion methods for a player as real as a physical
instrument. The application consists of two playing modes. The first
mode is free playing, a player can freely multi touches on wooden bar
to produce instrument sounds. The second mode is practicing mode
that guilds the player to follow percussions and rhythms of practice
songs. The application has achieved requirements and specifications.
Abstract: e-mail has become an important means of electronic
communication but the viability of its usage is marred by Unsolicited
Bulk e-mail (UBE) messages. UBE consists of many types
like pornographic, virus infected and 'cry-for-help' messages as well
as fake and fraudulent offers for jobs, winnings and medicines. UBE
poses technical and socio-economic challenges to usage of e-mails.
To meet this challenge and combat this menace, we need to
understand UBE. Towards this end, the current paper presents a
content-based textual analysis of more than 2700 body enhancement
medicinal UBE. Technically, this is an application of Text Parsing
and Tokenization for an un-structured textual document and we
approach it using Bag Of Words (BOW) and Vector Space Document
Model techniques. We have attempted to identify the most
frequently occurring lexis in the UBE documents that advertise
various products for body enhancement. The analysis of such top
100 lexis is also presented. We exhibit the relationship between
occurrence of a word from the identified lexis-set in the given UBE
and the probability that the given UBE will be the one advertising for
fake medicinal product. To the best of our knowledge and survey of
related literature, this is the first formal attempt for identification of
most frequently occurring lexis in such UBE by its textual analysis.
Finally, this is a sincere attempt to bring about alertness against and
mitigate the threat of such luring but fake UBE.
Abstract: The survey and classification of the different security
attacks in structured peer-to-peer (P2P) overlay networks can be
useful to computer system designers, programmers, administrators,
and users. In this paper, we attempt to provide a taxonomy of
structured P2P overlay networks security attacks. We have specially
focused on the way these attacks can arise at each level of the
network. Moreover, we observed that most of the existing systems
such as Content Addressable Network (CAN), Chord, Pastry,
Tapestry, Kademlia, and Viceroy suffer from threats and vulnerability
which lead to disrupt and corrupt their functioning. We hope that our
survey constitutes a good help for who-s working on this area of
research.
Abstract: A high performance computer includes a fast
processor and millions bytes of memory. During the data processing,
huge amount of information are shuffled between the memory and
processor. Because of its small size and its effectiveness speed, cache
has become a common feature of high performance computers.
Enhancing cache performance proved to be essential in the speed up
of cache-based computers. Most enhancement approaches can be
classified as either software based or hardware controlled. The
performance of the cache is quantified in terms of hit ratio or miss
ratio. In this paper, we are optimizing the cache performance based
on enhancing the cache hit ratio. The optimum cache performance is
obtained by focusing on the cache hardware modification in the way
to make a quick rejection to the missed line's tags from the hit-or
miss comparison stage, and thus a low hit time for the wanted line in
the cache is achieved. In the proposed technique which we called
Even- Odd Tabulation (EOT), the cache lines come from the main
memory into cache are classified in two types; even line's tags and
odd line's tags depending on their Least Significant Bit (LSB). This
division is exploited by EOT technique to reject the miss match line's
tags in very low time compared to the time spent by the main
comparator in the cache, giving an optimum hitting time for the
wanted cache line. The high performance of EOT technique against
the familiar mapping technique FAM is shown in the simulated
results.
Abstract: Cyber physical system (CPS) for target tracking, military surveillance, human health monitoring, and vehicle detection all require maximizing the utility and saving the energy. Sensor selection is one of the most important parts of CPS. Sensor selection problem (SSP) is concentrating to balance the tradeoff between the number of sensors which we used and the utility which we will get. In this paper, we propose a performance constrained slide windows (PCSW) based algorithm for SSP in CPS. we present results of extensive simulations that we have carried out to test and validate the PCSW algorithms when we track a target, Experiment shows that the PCSW based algorithm improved the performance including selecting time and communication times for selecting.
Abstract: This paper focuses on testing database of existing
information system. At the beginning we describe the basic problems
of implemented databases, such as data redundancy, poor design of
database logical structure or inappropriate data types in columns of
database tables. These problems are often the result of incorrect
understanding of the primary requirements for a database of an
information system. Then we propose an algorithm to compare the
conceptual model created from vague requirements for a database
with a conceptual model reconstructed from implemented database.
An algorithm also suggests steps leading to optimization of
implemented database. The proposed algorithm is verified by an
implemented prototype. The paper also describes a fuzzy system
which works with the vague requirements for a database of an
information system, procedure for creating conceptual from vague
requirements and an algorithm for reconstructing a conceptual model
from implemented database.
Abstract: Specification-based testing enables us to detect errors
in the implementation of functions defined in given specifications.
Its effectiveness in achieving high path coverage and efficiency in
generating test cases are always major concerns of testers. The automatic
test cases generation approach based on formal specifications
proposed by Liu and Nakajima is aimed at ensuring high effectiveness
and efficiency, but this approach has not been empirically assessed.
In this paper, we present an experiment for assessing Liu-s testing
approach. The result indicates that this testing approach may not be
effective in some circumstances. We discuss the result, analyse the
specific causes for the ineffectiveness, and describe some suggestions
for improvement.
Abstract: Since the conception of JML, many tools, applications and implementations have been done. In this context, the users or developers who want to use JML seem surounded by many of these tools, applications and so on. Looking for a common infrastructure and an independent language to provide a bridge between these tools and JML, we developed an approach to embedded contracts in XML for Java: XJML. This approach offer us the ability to separate preconditions, posconditions and class invariants using JML and XML, so we made a front-end which can process Runtime Assertion Checking, Extended Static Checking and Full Static Program Verification. Besides, the capabilities for this front-end can be extended and easily implemented thanks to XML. We believe that XJML is an easy way to start the building of a Graphic User Interface delivering in this way a friendly and IDE independency to developers community wich want to work with JML.
Abstract: Webcam systems now function as the new privileged
vantage points from which to view the city. This transformation of
CCTV technology from surveillance to promotional tool is significant
because its'scopic regime' presents, back to the public, a new virtual
'site' that sits alongside its real-time counterpart. Significantly,
thisraw 'image' data can, in fact,be co-optedand processed so as to
disrupt their original purpose. This paper will demonstrate this
disruptive capacity through an architectural project. It will reveal how
the adaption the webcam image offers a technical springboard by
which to initiate alternate urban form making decisions and subvert
the disciplinary reliance on the 'flat' orthographic plan. In so doing,
the paper will show how this 'digital material' exceeds the imagistic
function of the image; shiftingit from being a vehicle of signification
to a site of affect.
Abstract: This paper focuses on creating a component model of information system under uncertainty. The paper identifies problem in current approach of component modeling and proposes fuzzy tool, which will work with vague customer requirements and propose components of the resulting component model. The proposed tool is verified on specific information system and results are shown in paper. After finding suitable sub-components of the resulting component model, the component model is visualised by tool.
Abstract: e-Government is already in its second decade. Prerequisite for further development and adaptation to new realities is the optimal management of administrative information and knowledge production by those involved, i.e. the public sector, citizens and businesses. Nowadays, the amount of information displayed or distributed on the Internet has reached enormous dimensions, resulting in serious difficulties when extracting and managing knowledge. The semantic web is expected to play an important role in solving this problem and the technologies that support it. In this article, we address some relevant issues.
Abstract: In the past years a lot of effort has been made in the
field of face detection. The human face contains important features
that can be used by vision-based automated systems in order to
identify and recognize individuals. Face location, the primary step of
the vision-based automated systems, finds the face area in the input
image. An accurate location of the face is still a challenging task.
Viola-Jones framework has been widely used by researchers in order
to detect the location of faces and objects in a given image. Face
detection classifiers are shared by public communities, such as
OpenCV. An evaluation of these classifiers will help researchers to
choose the best classifier for their particular need. This work focuses
of the evaluation of face detection classifiers minding facial
landmarks.
Abstract: There are several approaches for handling multiclass classification. Aside from one-against-one (OAO) and one-against-all (OAA), hierarchical classification technique is also commonly used. A binary classification tree is a hierarchical classification structure that breaks down a k-class problem into binary sub-problems, each solved by a binary classifier. In each node, a set of classes is divided into two subsets. A good class partition should be able to group similar classes together. Many algorithms measure similarity in term of distance between class centroids. Classes are grouped together by a clustering algorithm when distances between their centroids are small. In this paper, we present a binary classification tree with tuned observation-based clustering (BCT-TOB) that finds a class partition by performing clustering on observations instead of class centroids. A merging step is introduced to merge any insignificant class split. The experiment shows that performance of BCT-TOB is comparable to other algorithms.
Abstract: This study proposes novel hybrid social network analysis and collaborative filtering approach to enhance the performance of recommender systems. The proposed model selects subgroups of users in Internet community through social network analysis (SNA), and then performs clustering analysis using the information about subgroups. Finally, it makes recommendations using cluster-indexing CF based on the clustering results. This study tries to use the cores in subgroups as an initial seed for a conventional clustering algorithm. This model chooses five cores which have the highest value of degree centrality from SNA, and then performs clustering analysis by using the cores as initial centroids (cluster centers). Then, the model amplifies the impact of friends in social network in the process of cluster-indexing CF.