Abstract: Fault-proneness of a software module is the
probability that the module contains faults. A correlation exists
between the fault-proneness of the software and the measurable
attributes of the code (i.e. the static metrics) and of the testing (i.e.
the dynamic metrics). Early detection of fault-prone software
components enables verification experts to concentrate their time and
resources on the problem areas of the software system under
development. This paper introduces Genetic Algorithm based
software fault prediction models with Object-Oriented metrics. The
contribution of this paper is that it has used Metric values of JEdit
open source software for generation of the rules for the classification
of software modules in the categories of Faulty and non faulty
modules and thereafter empirically validation is performed. The
results shows that Genetic algorithm approach can be used for
finding the fault proneness in object oriented software components.
Abstract: This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.
Abstract: Artificial Immune System (AIS) is relatively naive paradigm for intelligent computations. The inspiration for AIS is derived from natural Immune System (IS). Classically it is believed that IS strives to discriminate between self and non-self. Most of the existing AIS research is based on this approach. Danger Theory (DT) argues this approach and proposes that IS fights against danger producing elements and tolerates others. We, the computational researchers, are not concerned with the arguments among immunologists but try to extract from it novel abstractions for intelligent computation. This paper aims to follow DT inspiration for intelligent data processing. The approach may introduce new avenue in intelligent processing. The data used is system calls data that is potentially significant in intrusion detection applications.
Abstract: In this paper a new method is suggested for risk
management by the numerical patterns in data-mining. These patterns
are designed using probability rules in decision trees and are cared to
be valid, novel, useful and understandable. Considering a set of
functions, the system reaches to a good pattern or better objectives.
The patterns are analyzed through the produced matrices and some
results are pointed out. By using the suggested method the direction
of the functionality route in the systems can be controlled and best
planning for special objectives be done.
Abstract: XML is a markup language which is becoming the
standard format for information representation and data exchange. A
major purpose of XML is the explicit representation of the logical
structure of a document. Much research has been performed to
exploit logical structure of documents in information retrieval in
order to precisely extract user information need from large
collections of XML documents. In this paper, we describe an XML
information retrieval weighting scheme that tries to find the most
relevant elements in XML documents in response to a user query.
We present this weighting model for information retrieval systems
that utilize plausible inferences to infer the relevance of elements in
XML documents. We also add to this model the Dempster-Shafer
theory of evidence to express the uncertainty in plausible inferences
and Dempster-Shafer rule of combination to combine evidences
derived from different inferences.
Abstract: This paper presents an adaptive nonlinear position
controller with velocity constraint, capable of combining the
input-output linearization technique and Lyapunov stability theory.
Based on the Lyapunov stability theory, the adaptation law of the
proposed controller is derived along with the verification of the overall
system-s stability. Computer simulation results demonstrate that the
proposed controller is robust and it can ensure transient stability of
BLDCM, under the occurrence of a large sudden fault.
Abstract: An application framework provides a reusable design
and implementation for a family of software systems. Application
developers extend the framework to build their particular
applications using hooks. Hooks are the places identified to show
how to use and customize the framework. Hooks define Framework
Interface Classes (FICs) and their possible specifications, which
helps in building reusable test cases for the implementations of these
classes. In applications developed using gray-box frameworks, FICs
inherit framework classes or use them without inheritance. In this
paper, a test-case generation technique is extended to build test cases
for FICs built for gray-box frameworks. A tool is developed to
automate the introduced technique.
Abstract: As the Internet technology has developed rapidly, the
number of identities (IDs) managed by each individual person has
increased and various ID management technologies have been
developed to assist users. However, most of these technologies are
vulnerable to the existing hacking methods such as phishing attacks
and key-logging. If the administrator-s password is exposed, an
attacker can access the entire contents of the stolen user-s data files in
other devices. To solve these problems, we propose here a new ID
management scheme based on a Single Password Protocol. The paper
presents the details of the new scheme as well as a formal analysis of
the method using BAN Logic.
Abstract: Ranking of fuzzy numbers play an important role in
decision making, optimization, forecasting etc. Fuzzy numbers must
be ranked before an action is taken by a decision maker. In this
paper, with the help of several counter examples it is proved that
ranking method proposed by Chen and Chen (Expert Systems with
Applications 36 (2009) 6833-6842) is incorrect. The main aim of this
paper is to propose a new approach for the ranking of generalized
trapezoidal fuzzy numbers. The main advantage of the proposed
approach is that the proposed approach provide the correct ordering
of generalized and normal trapezoidal fuzzy numbers and also the
proposed approach is very simple and easy to apply in the real life
problems. It is shown that proposed ranking function satisfies all
the reasonable properties of fuzzy quantities proposed by Wang and
Kerre (Fuzzy Sets and Systems 118 (2001) 375-385).
Abstract: This paper introduces the effective speckle reduction of
synthetic aperture radar (SAR) images using inner product spaces in
undecimated wavelet domain. There are two major areas in projection
onto span algorithm where improvement can be made. First is the use
of undecimated wavelet transformation instead of discrete wavelet
transformation. And second area is the use of smoothing filter namely
directional smoothing filter which is an additional step. Proposed
method does not need any noise estimation and thresholding
technique. More over proposed method gives good results on both
single polarimetric and fully polarimetric SAR images.
Abstract: The steady state response of bond graphs representing
passive and active suspension is presented. A bond graph with
preferred derivative causality assignment to get the steady state
is proposed. A general junction structure of this bond graph
is proposed. The proposed methodology to passive and active
suspensions is applied.
Abstract: Crawling movement as a motive mode seen in nature
of some animals such as snakes possesses a specific syntactic and
dynamic analysis. Serpentine robot designed by inspiration from
nature and snake-s crawling motion, is regarded as a crawling robot.
In this paper, a serpentine robot with spiral motion model will be
analyzed. The purpose of this analysis is to calculate the vertical and
tangential forces along snake-s body and to determine the parameters
affecting on these forces. Two types of serpentine robots have been
designed in order to examine the achieved relations explained below.
Abstract: The hybridization of artificial immune system with
cellular automata (CA-AIS) is a novel method. In this hybrid model,
the cellular automaton within each cell deploys the artificial immune
system algorithm under optimization context in order to increase its
fitness by using its neighbor-s efforts. The hybrid model CA-AIS is
introduced to fix the standard artificial immune system-s weaknesses.
The credibility of the proposed approach is evaluated by simulations
and it shows that the proposed approach achieves better results
compared to standard artificial immune system.
Abstract: In this paper, a method to detect multiple ellipses is presented. The technique is efficient and robust against incomplete ellipses due to partial occlusion, noise or missing edges and outliers. It is an iterative technique that finds and removes the best ellipse until no reasonable ellipse is found. At each run, the best ellipse is extracted from randomly selected edge patches, its fitness calculated and compared to a fitness threshold. RANSAC algorithm is applied as a sampling process together with the Direct Least Square fitting of ellipses (DLS) as the fitting algorithm. In our experiment, the method performs very well and is robust against noise and spurious edges on both synthetic and real-world image data.
Abstract: The effect of different combinations of response
feedback on the performance of active control system on nonlinear
frames has been studied in this paper. To this end different feedback
combinations including displacement, velocity, acceleration and full
response feedback have been utilized in controlling the response of
an eight story bilinear hysteretic frame which has been subjected to a
white noise excitation and controlled by eight actuators which could
fully control the frame. For active control of nonlinear frame
Newmark nonlinear instantaneous optimal control algorithm has been
used which a diagonal matrix has been selected for weighting
matrices in performance index. For optimal design of active control
system while the objective has been to reduce the maximum drift to
below the yielding level, Distributed Genetic Algorithm (DGA) has
been used to determine the proper set of weighting matrices. The
criteria to assess the effect of each combination of response feedback
have been the minimum required control force to reduce the
maximum drift to below the yielding drift. The results of numerical
simulation show that the performance of active control system is
dependent on the type of response feedback where the velocity
feedback is more effective in designing optimal control system in
comparison with displacement and acceleration feedback. Also using
full feedback of response in controller design leads to minimum
control force amongst other combinations. Also the distributed
genetic algorithm shows acceptable convergence speed in solving the
optimization problem of designing active control systems.
Abstract: Encryption protects communication partners from
disclosure of their secret messages but cannot prevent traffic analysis
and the leakage of information about “who communicates with
whom". In the presence of collaborating adversaries, this linkability
of actions can danger anonymity. However, reliably providing
anonymity is crucial in many applications. Especially in contextaware
mobile business, where mobile users equipped with PDAs
request and receive services from service providers, providing
anonymous communication is mission-critical and challenging at the
same time. Firstly, the limited performance of mobile devices does
not allow for heavy use of expensive public-key operations which are
commonly used in anonymity protocols. Moreover, the demands for
security depend on the application (e.g., mobile dating vs. pizza
delivery service), but different users (e.g., a celebrity vs. a normal
person) may even require different security levels for the same
application. Considering both hardware limitations of mobile devices
and different sensitivity of users, we propose an anonymity
framework that is dynamically configurable according to user and
application preferences. Our framework is based on Chaum-s mixnet.
We explain the proposed framework, its configuration
parameters for the dynamic behavior and the algorithm to enforce
dynamic anonymity.
Abstract: Within the last years, several technologies have been developed to help building e-learning portals. Most of them follow approaches that deliver a vast amount of functionalities, suitable for class-like learning. The SuGI project, as part of the D-Grid (funded by the BMBF), targets on delivering a highly scalable and sustainable learning solution to provide materials (e.g. learning modules, training systems, webcasts, tutorials, etc.) containing knowledge about Grid computing to the D-Grid community. In this article, the process of the development of an e-learning portal focused on the requirements of this special user group is described. Furthermore, it deals with the conceptual and technical design of an e-learning portal, addressing the special needs of heterogeneous target groups. The main focus lies on the quality management of the software development process, Web templates for uploading new contents, the rich search and filter functionalities which will be described from a conceptual as well as a technical point of view. Specifically, it points out best practices as well as concepts to provide a sustainable solution to a relatively unknown and highly heterogeneous community.
Abstract: It has been shown that in most accidents the driver is responsible due to being distracted or misjudging the situation. In order to solve such problems research has been dedicated to developing driver assistance systems that are able to monitor the traffic situation around the vehicle. This paper presents methods for recognizing several circumstances on a road. The methods use both the in-vehicle warning systems and the roadside infrastructure. Preliminary evaluation results for fog and ice-on-road detection are presented. The ice detection results are based on data recorded in a test track dedicated to tyre friction testing. The achieved results anticipate that ice detection could work at a performance of 70% detection with the right setup, which is a good foundation for implementation. However, the full benefit of the presented cooperative system is achieved by fusing the outputs of multiple data sources, which is the key point of discussion behind this publication.
Abstract: In this paper, an Arabic letter recognition system based on Artificial Neural Networks (ANNs) and statistical analysis for feature extraction is presented. The ANN is trained using the Least Mean Squares (LMS) algorithm. In the proposed system, each typed Arabic letter is represented by a matrix of binary numbers that are used as input to a simple feature extraction system whose output, in addition to the input matrix, are fed to an ANN. Simulation results are provided and show that the proposed system always produces a lower Mean Squared Error (MSE) and higher success rates than the current ANN solutions.
Abstract: Frequently a group of people jointly decide and authorize
a specific person as a representative in some business/poitical
occasions, e.g., the board of a company authorizes the chief executive
officer to close a multi-billion acquisition deal. In this paper, an
integrated proxy multi-signature scheme that allows anonymously
vetoable delegation is proposed. This protocol integrates mechanisms
of private veto, distributed proxy key generation, secure transmission
of proxy key, and existentially unforgeable proxy multi-signature
scheme. First, a provably secure Guillou-Quisquater proxy signature
scheme is presented, then the “zero-sharing" protocol is extended
over a composite modulus multiplicative group, and finally the above
two are combined to realize the GQ proxy multi-signature with
anonymously vetoable delegation. As a proxy signature scheme, this
protocol protects both the original signers and the proxy signer.
The modular design allows simplified implementation with less
communication overheads and better computation performance than
a general secure multi-party protocol.