Abstract: Nowadays data backup format doesn-t cease to appear raising so the anxiety on their accessibility and their perpetuity. XML is one of the most promising formats to guarantee the integrity of data. This article suggests while showing one thing man can do with XML. Indeed XML will help to create a data backup model. The main task will consist in defining an application in JAVA able to convert information of a database in XML format and restore them later.
Abstract: We introduce a logic-based framework for database
updating under constraints. In our framework, the constraints are
represented as an instantiated extended logic program. When performing
an update, database consistency may be violated. We provide
an approach of maintaining database consistency, and study the
conditions under which the maintenance process is deterministic. We
show that the complexity of the computations and decision problems
presented in our framework is in each case polynomial time.
Abstract: With the rapid usage of portable devices mobility in
IP networks becomes more important issue in the recent years. IETF
standardized Mobile IP that works in Network Layer, which involves
tunneling of IP packets from HA to Foreign Agent. Mobile IP suffers
many problems of Triangular Routing, conflict with private
addressing scheme, increase in load in HA, need of permanent home
IP address, tunneling itself, and so on. In this paper, we proposed
mobility management in Application Layer protocol SIP and show
some comparative analysis between Mobile IP and SIP in context of
mobility.
Abstract: This paper presents a modified version of the
maximum urgency first scheduling algorithm. The maximum
urgency algorithm combines the advantages of fixed and dynamic
scheduling to provide the dynamically changing systems with
flexible scheduling. This algorithm, however, has a major
shortcoming due to its scheduling mechanism which may cause a
critical task to fail. The modified maximum urgency first scheduling
algorithm resolves the mentioned problem. In this paper, we propose
two possible implementations for this algorithm by using either
earliest deadline first or modified least laxity first algorithms for
calculating the dynamic priorities. These two approaches are
compared together by simulating the two algorithms. The earliest
deadline first algorithm as the preferred implementation is then
recommended. Afterwards, we make a comparison between our
proposed algorithm and maximum urgency first algorithm using
simulation and results are presented. It is shown that modified
maximum urgency first is superior to maximum urgency first, since it
usually has less task preemption and hence, less related overhead. It
also leads to less failed non-critical tasks in overloaded situations.
Abstract: The paper presents an approach for handling uncertain
information in deductive databases using multivalued logics. Uncertainty
means that database facts may be assigned logical values other
than the conventional ones - true and false. The logical values represent
various degrees of truth, which may be combined and propagated
by applying the database rules. A corresponding multivalued database
semantics is defined. We show that it extends successful conventional
semantics as the well-founded semantics, and has a polynomial time
data complexity.
Abstract: In this article, a formal specification and verification of the Rabin public-key scheme in a formal proof system is presented. The idea is to use the two views of cryptographic verification: the computational approach relying on the vocabulary of probability theory and complexity theory and the formal approach based on ideas and techniques from logic and programming languages. A major objective of this article is the presentation of the first computer-proved implementation of the Rabin public-key scheme in Isabelle/HOL. Moreover, we explicate a (computer-proven) formalization of correctness as well as a computer verification of security properties using a straight-forward computation model in Isabelle/HOL. The analysis uses a given database to prove formal properties of our implemented functions with computer support. The main task in designing a practical formalization of correctness as well as efficient computer proofs of security properties is to cope with the complexity of cryptographic proving. We reduce this complexity by exploring a light-weight formalization that enables both appropriate formal definitions as well as efficient formal proofs. Consequently, we get reliable proofs with a minimal error rate augmenting the used database, what provides a formal basis for more computer proof constructions in this area.
Abstract: There are two paradigms proposed to provide QoS for Internet applications: Integrated service (IntServ) and Differentiated service (DiffServ).Intserv is not appropriate for large network like Internet. Because is very complex. Therefore, to reduce the complexity of QoS management, DiffServ was introduced to provide QoS within a domain using aggregation of flow and per- class service. In theses networks QoS between classes is constant and it allows low priority traffic to be effected from high priority traffic, which is not suitable. In this paper, we proposed a fuzzy controller, which reduced the effect of low priority class on higher priority ones. Our simulations shows that, our approach reduces the latency dependency of low priority class on higher priority ones, in an effective manner.
Abstract: This paper deals with a power-conscious ANDEXOR- Inverter type logic implementation for a complex class of Boolean functions, namely Achilles- heel functions. Different variants of the above function class have been considered viz. positive, negative and pure horn for analysis and simulation purposes. The proposed realization is compared with the decomposed implementation corresponding to an existing standard AND-EXOR logic minimizer; both result in Boolean networks with good testability attribute. It could be noted that an AND-OR-EXOR type logic network does not exist for the positive phase of this unique class of logic function. Experimental results report significant savings in all the power consumption components for designs based on standard cells pertaining to a 130nm UMC CMOS process The simulations have been extended to validate the savings across all three library corners (typical, best and worst case specifications).
Abstract: In this paper we present a new approach to detecting a
flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image
based on texture features. Texture is one of the most important
features used in recognizing patterns in an image. The paper
describes texture features based on 2D Gabor functions, i.e.,
Gaussian shaped band-pass filters, with dyadic treatment of the radial
spatial frequency range and multiple orientations, which represent an
appropriate choice for tasks requiring simultaneous measurement in
both space and frequency domains. The most relevant features are
used as input data on a Fuzzy c-mean clustering classifier. The
classes that exist are only two: 'defects' or 'no defects'. The proposed
approach is tested on the T.O.F.D image achieved at the laboratory
and on the industrial field.
Abstract: One of the most used assumptions in logic programming
and deductive databases is the so-called Closed World Assumption
(CWA), according to which the atoms that cannot be inferred
from the programs are considered to be false (i.e. a pessimistic
assumption). One of the most successful semantics of conventional
logic programs based on the CWA is the well-founded semantics.
However, the CWA is not applicable in all circumstances when
information is handled. That is, the well-founded semantics, if
conventionally defined, would behave inadequately in different cases.
The solution we adopt in this paper is to extend the well-founded
semantics in order for it to be based also on other assumptions. The
basis of (default) negative information in the well-founded semantics
is given by the so-called unfounded sets. We extend this concept
by considering optimistic, pessimistic, skeptical and paraconsistent
assumptions, used to complete missing information from a program.
Our semantics, called extended well-founded semantics, expresses
also imperfect information considered to be missing/incomplete,
uncertain and/or inconsistent, by using bilattices as multivalued
logics. We provide a method of computing the extended well-founded
semantics and show that Kripke-Kleene semantics is captured by
considering a skeptical assumption. We show also that the complexity
of the computation of our semantics is polynomial time.
Abstract: We provide a supervised speech-independent voice recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification method uses a special nonlinear metric, derived from the Hausdorff distance for sets, and a minimum mean distance classifier.
Abstract: This paper proposes a scheduling scheme using feedback
control to reduce the response time of aperiodic tasks with soft
real-time constraints. We design an algorithm based on the proposed
scheduling scheme and Total Bandwidth Server (TBS) that is a
conventional server technique for scheduling aperiodic tasks. We then
describe the feedback controller of the algorithm and give the control
parameter tuning methods. The simulation study demonstrates that the
algorithm can reduce the mean response time up to 26% compared
to TBS in exchange for slight deadline misses.
Abstract: Previously, harmonic parameters (HPs) have been
selected as features extracted from EEG signals for automatic sleep
scoring. However, in previous studies, only one HP parameter was
used, which were directly extracted from the whole epoch of EEG
signal.
In this study, two different transformations were applied to extract
HPs from EEG signals: Hilbert-Huang transform (HHT) and wavelet
transform (WT). EEG signals are decomposed by the two
transformations; and features were extracted from different
components. Twelve parameters (four sets of HPs) were extracted.
Some of the parameters are highly diverse among different stages.
Afterward, HPs from two transformations were used to building a
rough sleep stages scoring model using the classifier SVM. The
performance of this model is about 78% using the features obtained by
our proposed extractions. Our results suggest that these features may
be useful for automatic sleep stages scoring.
Abstract: In this paper, we propose a face recognition algorithm
using AAM and Gabor features. Gabor feature vectors which are well
known to be robust with respect to small variations of shape, scaling,
rotation, distortion, illumination and poses in images are popularly
employed for feature vectors for many object detection and
recognition algorithms. EBGM, which is prominent among face
recognition algorithms employing Gabor feature vectors, requires
localization of facial feature points where Gabor feature vectors are
extracted. However, localization method employed in EBGM is based
on Gabor jet similarity and is sensitive to initial values. Wrong
localization of facial feature points affects face recognition rate. AAM
is known to be successfully applied to localization of facial feature
points. In this paper, we devise a facial feature point localization
method which first roughly estimate facial feature points using AAM
and refine facial feature points using Gabor jet similarity-based facial
feature localization method with initial points set by the rough facial
feature points obtained from AAM, and propose a face recognition
algorithm using the devised localization method for facial feature
localization and Gabor feature vectors. It is observed through
experiments that such a cascaded localization method based on both
AAM and Gabor jet similarity is more robust than the localization
method based on only Gabor jet similarity. Also, it is shown that the
proposed face recognition algorithm using this devised localization
method and Gabor feature vectors performs better than the
conventional face recognition algorithm using Gabor jet
similarity-based localization method and Gabor feature vectors like
EBGM.
Abstract: Among other factors that characterize satellite communication
channels is their high bit error rate. We present a system for
still image transmission over noisy satellite channels. The system
couples image compression together with error control codes to
improve the received image quality while maintaining its bandwidth
requirements. The proposed system is tested using a high resolution
satellite imagery simulated over the Rician fading channel. Evaluation
results show improvement in overall system including image quality
and bandwidth requirements compared to similar systems with different
coding schemes.
Abstract: Eye localization is necessary for face recognition and
related application areas. Most of eye localization algorithms reported
so far still need to be improved about precision and computational
time for successful applications. In this paper, we propose an eye
location method based on multi-scale Gabor feature vectors, which is
more robust with respect to initial points. The eye localization based
on Gabor feature vectors first needs to constructs an Eye Model Bunch
for each eye (left or right eye) which consists of n Gabor jets and
average eye coordinates of each eyes obtained from n model face
images, and then tries to localize eyes in an incoming face image by
utilizing the fact that the true eye coordinates is most likely to be very
close to the position where the Gabor jet will have the best Gabor jet
similarity matching with a Gabor jet in the Eye Model Bunch. Similar
ideas have been already proposed in such as EBGM (Elastic Bunch
Graph Matching). However, the method used in EBGM is known to be
not robust with respect to initial values and may need extensive search
range for achieving the required performance, but extensive search
ranges will cause much more computational burden. In this paper, we
propose a multi-scale approach with a little increased computational
burden where one first tries to localize eyes based on Gabor feature
vectors in a coarse face image obtained from down sampling of the
original face image, and then localize eyes based on Gabor feature
vectors in the original resolution face image by using the eye
coordinates localized in the coarse scaled image as initial points.
Several experiments and comparisons with other eye localization
methods reported in the other papers show the efficiency of our
proposed method.
Abstract: A cancelable palmprint authentication system
proposed in this paper is specifically designed to overcome the
limitations of the contemporary biometric authentication system. In
this proposed system, Geometric and pseudo Zernike moments are
employed as feature extractors to transform palmprint image into a
lower dimensional compact feature representation. Before moment
computation, wavelet transform is adopted to decompose palmprint
image into lower resolution and dimensional frequency subbands.
This reduces the computational load of moment calculation
drastically. The generated wavelet-moment based feature
representation is used to generate cancelable verification key with a
set of random data. This private binary key can be canceled and
replaced. Besides that, this key also possesses high data capture
offset tolerance, with highly correlated bit strings for intra-class
population. This property allows a clear separation of the genuine
and imposter populations, as well as zero Equal Error Rate
achievement, which is hardly gained in the conventional biometric
based authentication system.
Abstract: In this work, we are interested in developing a speech denoising tool by using a discrete wavelet packet transform (DWPT). This speech denoising tool will be employed for applications of recognition, coding and synthesis. For noise reduction, instead of applying the classical thresholding technique, some wavelet packet nodes are set to zero and the others are thresholded. To estimate the non stationary noise level, we employ the spectral entropy. A comparison of our proposed technique to classical denoising methods based on thresholding and spectral subtraction is made in order to evaluate our approach. The experimental implementation uses speech signals corrupted by two sorts of noise, white and Volvo noises. The obtained results from listening tests show that our proposed technique is better than spectral subtraction. The obtained results from SNR computation show the superiority of our technique when compared to the classical thresholding method using the modified hard thresholding function based on u-law algorithm.
Abstract: The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.
Abstract: 2007 is a jubilee year: in 1967, programming language SIMULA 67 was presented, which contained all aspects of what was later called object-oriented programming. The present paper contains a description of the development unto the objectoriented programming, the role of simulation in this development and other tools that appeared in SIMULA 67 and that are nowadays called super-object-oriented programming.