Abstract: The aim of software maintenance is to maintain
the software system in accordance with advancement in software
and hardware technology. One of the early works on software
maintenance is to extract information at higher level of abstraction. In
this paper, we present the process of how to design an information
extraction tool for software maintenance. The tool can extract the
basic information from old programs such as about variables, based
classes, derived classes, objects of classes, and functions. The tool
have two main parts; the lexical analyzer module that can read the
input file character by character, and the searching module which
users can get the basic information from the existing programs. We
implemented this tool for a patterned sub-C++ language as an input
file.
Abstract: R.C.C. buildings with dual structural system
consisting of shear walls (or braces) and moment resisting frames
have been widely used to resist lateral forces during earthquakes. The
dual systems are designed to resist the total design lateral force in
proportion to their lateral stiffness. The response of combination of
braces and shear walls has not yet been studied. The combination
may prove to be more effective to resist lateral forces during
earthquakes. This concept has been applied to regular R.C.C.
buildings provided with shear walls, braces and their combinations.
Abstract: These days customer satisfaction plays vital role in
any business. When customer searches for a product, significantly a
junk of irrelevant information is what is given, leading to customer
dissatisfaction. To provide exactly relevant information on the
searched product, we are proposing a model of KaaS (Knowledge as
a Service), which pre-processes the information using decision
making paradigm using Multi-agents.
Information obtained from various sources is taken to derive
knowledge and they are linked to Cloud to capture new idea. The
main focus of this work is to acquire relevant information
(knowledge) related to product, then convert this knowledge into a
service for customer satisfaction and deploy on cloud.
For achieving these objectives we are have opted to use multi
agents. They are communicating and interacting with each other,
manipulate information, provide knowledge, to take decisions. The
paper discusses about KaaS as an intelligent approach for Knowledge
acquisition.
Abstract: A model was constructed to predict the amount of
solar radiation that will make contact with the surface of the earth in
a given location an hour into the future. This project was supported
by the Southern Company to determine at what specific times during
a given day of the year solar panels could be relied upon to produce
energy in sufficient quantities. Due to their ability as universal
function approximators, an artificial neural network was used to
estimate the nonlinear pattern of solar radiation, which utilized
measurements of weather conditions collected at the Griffin, Georgia
weather station as inputs. A number of network configurations and
training strategies were utilized, though a multilayer perceptron with
a variety of hidden nodes trained with the resilient propagation
algorithm consistently yielded the most accurate predictions. In
addition, a modeled direct normal irradiance field and adjacent
weather station data were used to bolster prediction accuracy. In later
trials, the solar radiation field was preprocessed with a discrete
wavelet transform with the aim of removing noise from the
measurements. The current model provides predictions of solar
radiation with a mean square error of 0.0042, though ongoing efforts
are being made to further improve the model’s accuracy.
Abstract: This paper presents development results of the method
of seismoacoustic activity monitoring based on usage vibrosensitive
properties of optical fibers. Analysis of Rayleigh backscattering
radiation parameters changes, which take place due to microscopic
seismoacoustic impacts on the optical fiber, allows to determine
seismoacoustic emission sources positions and to identify their types.
Results of using this approach are successful for complex monitoring
of railways.
Abstract: For optimal unbiased filter as mean-square and in the
case of functioning anomalous noises in the observation memory
channel, we have proved insensitivity of filter to inaccurate
knowledge of the anomalous noise intensity matrix and its
equivalence to truncated filter plotted only by non anomalous
components of an observation vector.
Abstract: In this paper, we will give a cryptographic application
over the integral closure O_Lof sextic extension L, namely L is an
extension of Q of degree 6 in the form Q(a,b), which is a rational
quadratic and monogenic extension over a pure monogenic cubic
subfield K generated by a who is a root of monic irreducible
polynomial of degree 2 andb is a root of irreducible polynomial of
degree 3.
Abstract: This article discusses event monitoring options for
heterogeneous event sources as they are given in nowadays
heterogeneous distributed information systems. It follows the central
assumption, that a fully generic event monitoring solution cannot
provide complete support for event monitoring; instead, event source
specific semantics such as certain event types or support for certain
event monitoring techniques have to be taken into account.
Following from this, the core result of the work presented here is
the extension of a configurable event monitoring (Web) service for a
variety of event sources. A service approach allows us to trade
genericity for the exploitation of source specific characteristics. It
thus delivers results for the areas of SOA, Web services, CEP and
EDA.
Abstract: Image segmentation plays an important role in
medical imaging applications. Therefore, accurate methods are
needed for the successful segmentation of medical images for
diagnosis and detection of various diseases. In this paper, we have
used maximum entropy to achieve image segmentation. Maximum
entropy has been calculated using Shannon, Renyi and Tsallis
entropies. This work has novelty based on the detection of skin lesion
caused by the bite of a parasite called Sand Fly causing the disease is
called Cutaneous Leishmaniasis.
Abstract: In order to protect data privacy, image with sensitive or
private information needs to be encrypted before being outsourced to
the cloud. However, this causes difficulties in image retrieval and data
management. A secure image retrieval method based on orthogonal
decomposition is proposed in the paper. The image is divided into two
different components, for which encryption and feature extraction are
executed separately. As a result, cloud server can extract features from
an encrypted image directly and compare them with the features of the
queried images, so that the user can thus obtain the image. Different
from other methods, the proposed method has no special requirements
to encryption algorithms. Experimental results prove that the proposed
method can achieve better security and better retrieval precision.
Abstract: Many organizations are investing in web applications
and technologies in order to be competitive, some of them could not
achieve its goals. The quality of web-based applications could play
an important role for organizations to be competitive. So the aim of
this study is to investigate the impact of quality of web-based
applications to achieve a competitive advantage. A new model has
been developed. An empirical investigation was performed on a
banking sector in Jordan to test the new model. The results show that
impact of web-based applications on competitive advantage is
significant. Finally, further work is planned to validate and evaluate
the proposed model using several domains.
Abstract: This paper presents a novel integrated hybrid
approach for fault diagnosis (FD) of nonlinear systems. Unlike most
FD techniques, the proposed solution simultaneously accomplishes
fault detection, isolation, and identification (FDII) within a unified
diagnostic module. At the core of this solution is a bank of adaptive
neural parameter estimators (NPE) associated with a set of singleparameter
fault models. The NPEs continuously estimate unknown
fault parameters (FP) that are indicators of faults in the system. Two
NPE structures including series-parallel and parallel are developed
with their exclusive set of desirable attributes. The parallel scheme is
extremely robust to measurement noise and possesses a simpler, yet
more solid, fault isolation logic. On the contrary, the series-parallel
scheme displays short FD delays and is robust to closed-loop system
transients due to changes in control commands. Finally, a fault
tolerant observer (FTO) is designed to extend the capability of the
NPEs to systems with partial-state measurement.
Abstract: Taiwan is a hyper endemic area for the Hepatitis B
virus (HBV). The estimated total number of HBsAg carriers in the
general population who are more than 20 years old is more than 3
million. Therefore, a case record review is conducted from January
2003 to June 2007 for all patients with a diagnosis of acute hepatitis
who were admitted to the Emergency Department (ED) of a
well-known teaching hospital. The cost for the use of medical
resources is defined as the total medical fee. In this study, principal
component analysis (PCA) is firstly employed to reduce the number of
dimensions. Support vector regression (SVR) and artificial neural
network (ANN) are then used to develop the forecasting model. A total
of 117 patients meet the inclusion criteria. 61% patients involved in
this study are hepatitis B related. The computational result shows that
the proposed PCA-SVR model has superior performance than other
compared algorithms. In conclusion, the Child-Pugh score and
echogram can both be used to predict the cost of medical resources for
patients with acute hepatitis in the ED.
Abstract: We have conducted the optimal synthesis of rootmean-
squared objective filter to estimate the state vector in the case if
within the observation channel with memory the anomalous noises
with unknown mathematical expectation are complement in the
function of the regular noises. The synthesis has been carried out for
linear stochastic systems of continuous - time.
Abstract: This paper is concerned with knowledge representation
and extraction of fuzzy if-then rules using Interval Type-2
Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of
fuzzy granulation. This proposed clustering algorithm is based on
information granulation in the form of IT2 based Fuzzy C-Means
(IT2-FCM) clustering and estimates the cluster centers by preserving
the homogeneity between the clustered patterns from the IT2 contexts
produced in the output space. Furthermore, we can obtain the
automatic knowledge representation in the design of Radial Basis
Function Networks (RBFN), Linguistic Model (LM), and Adaptive
Neuro-Fuzzy Networks (ANFN) from the numerical input-output data
pairs. We shall focus on a design of ANFN in this paper. The
experimental results on an estimation problem of energy performance
reveal that the proposed method showed a good knowledge
representation and performance in comparison with the previous
works.
Abstract: The distribution of a single global clock across a chip
has become the major design bottleneck for high performance VLSI
systems owing to the power dissipation, process variability and multicycle
cross-chip signaling. A Network-on-Chip (NoC) architecture
partitioned into several synchronous blocks has become a promising
approach for attaining fine-grain power management at the system
level. In a NoC architecture the communication between the blocks is
handled asynchronously. To interface these blocks on a chip
operating at different frequencies, an asynchronous FIFO interface is
inevitable. However, these asynchronous FIFOs are not required if
adjacent blocks belong to the same clock domain. In this paper, we
have designed and analyzed a 16-bit asynchronous micropipelined
FIFO of depth four, with the awareness of place and route on an
FPGA device. We have used a commercially available Spartan 3
device and designed a high speed implementation of the
asynchronous 4-phase micropipeline. The asynchronous FIFO
implemented on the FPGA device shows 76 Mb/s throughput and a
handshake cycle of 109 ns for write and 101.3 ns for read at the
simulation under the worst case operating conditions (voltage =
0.95V) on a working chip at the room temperature.
Abstract: The article deals with the tool in Matlab GUI form
that is designed to analyse a mechatronic system sensitivity and
tolerance. In the analysed mechatronic system, a torque is transferred
from the drive to the load through a coupling containing flexible
elements. Different methods of control system design are used. The
classic form of the feedback control is proposed using Naslin method,
modulus optimum criterion and inverse dynamics method. The
cascade form of the control is proposed based on combination of
modulus optimum criterion and symmetric optimum criterion. The
sensitivity is analysed on the basis of absolute and relative sensitivity
of system function to the change of chosen parameter value of the
mechatronic system, as well as the control subsystem. The tolerance
is analysed in the form of determining the range of allowed relative
changes of selected system parameters in the field of system stability.
The tool allows to analyse an influence of torsion stiffness, torsion
damping, inertia moments of the motor and the load and controller(s)
parameters. The sensitivity and tolerance are monitored in terms of
the impact of parameter change on the response in the form of system
step response and system frequency-response logarithmic
characteristics. The Symbolic Math Toolbox for expression of the
final shape of analysed system functions was used. The sensitivity
and tolerance are graphically represented as 2D graph of sensitivity
or tolerance of the system function and 3D/2D static/interactive graph
of step/frequency response.
Abstract: Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FPgrowth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.
Abstract: Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.
Abstract: Grid is an environment with millions of resources
which are dynamic and heterogeneous in nature. A computational
grid is one in which the resources are computing nodes and is meant
for applications that involves larger computations. A scheduling
algorithm is said to be efficient if and only if it performs better
resource allocation even in case of resource failure. Resource
allocation is a tedious issue since it has to consider several
requirements such as system load, processing cost and time, user’s
deadline and resource failure. This work attempts in designing a
resource allocation algorithm which is cost-effective and also targets
at load balancing, fault tolerance and user satisfaction by considering
the above requirements. The proposed Budget Constrained Load
Balancing Fault Tolerant algorithm with user satisfaction (BLBFT)
reduces the schedule makespan, schedule cost and task failure rate
and improves resource utilization. Evaluation of the proposed
BLBFT algorithm is done using Gridsim toolkit and the results are
compared with the algorithms which separately concentrates on all
these factors. The comparison results ensure that the proposed
algorithm works better than its counterparts.