Abstract: In aircraft applications, according to the nature of
electrical equipment its location may be in unpressurized area or very
close to the engine; thus, the environmental conditions may change
from atmospheric pressure to less than 100 mbar, and the temperature
may be higher than the ambient one as in most real working
conditions of electrical equipment. Then, the classical Paschen curve
has to be replotted since these parameters may affect the discharge
ignition voltage. In this paper, we firstly investigate the domain of
validity of two corrective expressions on the Paschen-s law found in
the literature, in case of changing the air environment and known as
Peek and Dunbar corrections. Results show that these corrections are
no longer valid for combined variation of temperature and pressure.
After that, a new empirical expression for breakdown voltage is
proposed and is validated in the case of combined variations of
temperature and pressure.
Abstract: Data gathering is an essential operation in wireless
sensor network applications. So it requires energy efficiency
techniques to increase the lifetime of the network. Similarly,
clustering is also an effective technique to improve the energy
efficiency and network lifetime of wireless sensor networks. In this
paper, an energy efficient cluster formation protocol is proposed with
the objective of achieving low energy dissipation and latency without
sacrificing application specific quality. The objective is achieved by
applying randomized, adaptive, self-configuring cluster formation
and localized control for data transfers. It involves application -
specific data processing, such as data aggregation or compression.
The cluster formation algorithm allows each node to make
independent decisions, so as to generate good clusters as the end.
Simulation results show that the proposed protocol utilizes minimum
energy and latency for cluster formation, there by reducing the
overhead of the protocol.
Abstract: Data clustering is an important data exploration
technique with many applications in data mining. The k-means
algorithm is well known for its efficiency in clustering large data
sets. However, this algorithm is suitable for spherical shaped clusters
of similar sizes and densities. The quality of the resulting clusters
decreases when the data set contains spherical shaped with large
variance in sizes. In this paper, we introduce a competent procedure
to overcome this problem. The proposed method is based on shifting
the center of the large cluster toward the small cluster, and recomputing
the membership of small cluster points, the experimental
results reveal that the proposed algorithm produces satisfactory
results.
Abstract: With increasing data in medical databases, medical
data retrieval is growing in popularity. Some of this analysis
including inducing propositional rules from databases using many
soft techniques, and then using these rules in an expert system.
Diagnostic rules and information on features are extracted from
clinical databases on diseases of congenital anomaly. This paper
explain the latest soft computing techniques and some of the
adaptive techniques encompasses an extensive group of methods
that have been applied in the medical domain and that are used for
the discovery of data dependencies, importance of features,
patterns in sample data, and feature space dimensionality
reduction. These approaches pave the way for new and interesting
avenues of research in medical imaging and represent an important
challenge for researchers.
Abstract: The lecture represents significant advances in
understanding of the transfer processes mechanism in turbulent
separated flows. Based upon experimental data suggesting the
governing role of generated local pressure gradient that takes place in
the immediate vicinity of the wall in separated flow as a result of
intense instantaneous accelerations induced by large-scale vortex
flow structures similarity laws for mean velocity and temperature and
spectral characteristics and heat and mass transfer law for turbulent
separated flows have been developed. These laws are confirmed by
available experimental data. The results obtained were employed for
analysis of heat and mass transfer in some very complex processes
occurring in technological applications such as impinging jets, heat
transfer of cylinders in cross flow and in tube banks, packed beds
where processes manifest distinct properties which allow them to be
classified under turbulent separated flows. Many facts have got an
explanation for the first time.
Abstract: The demand for autonomous resource
management for distributed systems has increased in recent
years. Distributed systems require an efficient and powerful
communication mechanism between applications running on
different hosts and networks. The use of mobile agent
technology to distribute and delegate management tasks
promises to overcome the scalability and flexibility limitations
of the currently used centralized management approach. This
work proposes a multiagent system that adopts mobile agents
as a technology for tasks distribution, results collection, and
management of resources in large-scale distributed systems. A
new mobile agent-based approach for collecting results from
distributed system elements is presented. The technique of
artificial intelligence based on intelligent agents giving the
system a proactive behavior. The presented results are based
on a design example of an application operating in a mobile
environment.
Abstract: The present work deals with optimization of cascade refrigeration system using eco friendly refrigerants pair R507A and R23. R507A is azeotropic mixture composed of HFC refrigerants R125/R143a (50%/50% by wt.). R23 is a single component HFC refrigerant used as replacement to CFC refrigerant R13 in low temperature applications. These refrigerants have zero ozone depletion potential and are non-flammable. Optimization of R507AR23 cascade refrigeration system performance parameters such as minimum work required, refrigeration effect, coefficient of performance and exergetic efficiency was carried out in terms of eight operating parameters- combinations using Genetic Algorithm tool. The eight operating parameters include (1) low side evaporator temperature (2) high side condenser temperature (3) temperature difference in the cascade heat exchanger (4) low side condenser temperature (5) low side degree of subcooling (6) high side degree of subcooling (7) low side degree of superheating (8) high side degree of superheating. Results show that for minimum work system should operate at high temperature in low side evaporator, low temperature in high side condenser, low temperature difference in cascade condenser, high temperature in low side condenser and low degree of subcooling and superheating in both side. For maximum refrigeration effect system should operate at high temperature in low side evaporator, high temperature in high side condenser, high temperature difference in cascade condenser, low temperature in low side condenser and higher degree of subcooling in LT and HT side. For maximum coefficient of performance and exergetic efficiency, system should operate at high temperature in low side evaporator, low temperature in high side condenser, low temperature difference in cascade condenser, high temperature in low side condenser and higher degree of subcooling and superheating in low side of the system.
Abstract: The chemistry of sulphone hydrazide has gained increase interest in both synthetic organic chemistry and biological fields and has considerable value. The therapeutic importance of these compounds is the attractive force to continue research in such a point. The present review covers the literature up to date for the synthesis, reactions and applications of such compounds.
Abstract: Data mining, which is the exploration of
knowledge from the large set of data, generated as a result of
the various data processing activities. Frequent Pattern Mining
is a very important task in data mining. The previous
approaches applied to generate frequent set generally adopt
candidate generation and pruning techniques for the
satisfaction of the desired objective. This paper shows how
the different approaches achieve the objective of frequent
mining along with the complexities required to perform the
job. This paper will also look for hardware approach of cache
coherence to improve efficiency of the above process. The
process of data mining is helpful in generation of support
systems that can help in Management, Bioinformatics,
Biotechnology, Medical Science, Statistics, Mathematics,
Banking, Networking and other Computer related
applications. This paper proposes the use of both upward and
downward closure property for the extraction of frequent item
sets which reduces the total number of scans required for the
generation of Candidate Sets.
Abstract: A simple approach is demonstrated for growing large
scale, nearly vertically aligned ZnO nanowire arrays by thermal
oxidation method. To reveal effect of temperature on growth and
physical properties of the ZnO nanowires, gold coated zinc substrates
were annealed at 300 °C and 400 °C for 4 hours duration in air. Xray
diffraction patterns of annealed samples indicated a set of well
defined diffraction peaks, indexed to the wurtzite hexagonal phase of
ZnO. The scanning electron microscopy studies show formation of
ZnO nanowires having length of several microns and average of
diameter less than 500 nm. It is found that the areal density of wires
is relatively higher, when the annealing is carried out at higher
temperature i.e. at 400°C. From the field emission studies, the values
of the turn-on and threshold field, required to draw emission current
density of 10 μA/cm2 and 100 μA/cm2 are observed to be 1.2 V/μm
and 1.7 V/μm for the samples annealed at 300 °C and 2.9 V/μm and
3.7 V/μm for that annealed at 400 °C, respectively. The field
emission current stability, investigated over duration of more than 2
hours at the preset value of 1 μA, is found to be fairly good in both
cases. The simplicity of the synthesis route coupled with the
promising field emission properties offer unprecedented advantage
for the use of ZnO field emitters for high current density
applications.
Abstract: Medical applications are among the most impactful
areas of microrobotics. The ultimate goal of medical microrobots is
to reach currently inaccessible areas of the human body and carry out
a host of complex operations such as minimally invasive surgery
(MIS), highly localized drug delivery, and screening for diseases at
their very early stages. Miniature, safe and efficient propulsion
systems hold the key to maturing this technology but they pose
significant challenges. A new type of propulsion developed recently,
uses multi-flagella architecture inspired by the motility mechanism of
prokaryotic microorganisms. There is a lack of efficient methods for
designing this type of propulsion system. The goal of this paper is to
overcome the lack and this way, a numerical strategy is proposed to
design multi-flagella propulsion systems. The strategy is based on the
implementation of the regularized stokeslet and rotlet theory, RFT
theory and new approach of “local corrected velocity". The effects of
shape parameters and angular velocities of each flagellum on overall
flow field and on the robot net forces and moments are considered.
Then a multi-layer perceptron artificial neural network is designed
and employed to adjust the angular velocities of the motors for
propulsion control. The proposed method applied successfully on a
sample configuration and useful demonstrative results is obtained.
Abstract: This work aims to reduce the read power consumption
as well as to enhance the stability of the SRAM cell during the read
operation. A new 10-transisor cell is proposed with a new read
scheme to minimize the power consumption within the memory core.
It has separate read and write ports, thus cell read stability is
significantly improved. A 16Kb SRAM macro operating at 1V
supply voltage is demonstrated in 65 nm CMOS process. Its read
power consumption is reduced to 24% of the conventional design.
The new cell also has lower leakage current due to its special bit-line
pre-charge scheme. As a result, it is suitable for low-power mobile
applications where power supply is restricted by the battery.
Abstract: Mobile payments have been deployed by businesses for more than a decade. Customers use mobile payments if they trust in this relatively new payment method, have a belief and confidence in, as well as reliance on its services and applications. Despite its potential, the current literature shows that there is lack of customer trust in B2C mobile payments, and a lack of studies that determine the factors that influence their trust in these payments; which make these factors yet to be understood, especially in the Middle East region. Thus, this study aims to explore the factors that influence customer trust in mobile payments. The empirical data for this explorative study was collected by establishing four focus group sessions in the UAE. The results indicate that the explored significant factors can be classified into five main groups: customer characteristics, environmental (social and cultural) influences, provider characteristics, mobile-device characteristics, and perceived risks.
Abstract: Wireless sensor networks is an emerging technology
that serves as environment monitors in many applications. Yet
these miniatures suffer from constrained resources in terms of
computation capabilities and energy resources. Limited energy
resource in these nodes demands an efficient consumption of that
resource either by developing the modules itself or by providing
an efficient communication protocols. This paper presents a
comprehensive summarization and a comparative study of the
available MAC protocols proposed for Wireless Sensor Networks
showing their capabilities and efficiency in terms of energy
consumption and delay guarantee.
Abstract: In this paper is to evaluate audio and speech quality
with the help of Digital Audio Watermarking Technique under the
different types of attacks (signal impairments) like Gaussian Noise,
Compression Error and Jittering Effect. Further attacks are
considered as Hostile Environment. Audio and Speech Quality
Evaluation is an important research topic. The traditional way for
speech quality evaluation is using subjective tests. They are reliable,
but very expensive, time consuming, and cannot be used in certain
applications such as online monitoring. Objective models, based on
human perception, were developed to predict the results of subjective
tests. The existing objective methods require either the original
speech or complicated computation model, which makes some
applications of quality evaluation impossible.
Abstract: Unlike the best effort service provided by the internet
today, next-generation wireless networks will support real-time
applications. This paper proposes an adaptive early packet discard
(AEPD) policy to improve the performance of the real time TCP
traffic over ATM networks and avoid the fragmentation problem.
Three main aspects are incorporated in the proposed policy. First,
providing quality-of-service (QoS) guaranteed for real-time
applications by implementing a priority scheduling. Second,
resolving the partially corrupted packets problem by differentiating
the buffered cells of one packet from another. Third, adapting a
threshold dynamically using Fuzzy logic based on the traffic
behavior to maintain a high throughput under a variety of load
conditions. The simulation is run for two priority classes of the input
traffic: real time and non-real time classes. Simulation results show
that the proposed AEPD policy improves throughput and fairness
over that using static threshold under the same traffic conditions.
Abstract: Ontologies play an important role in semantic web applications and are often developed by different groups and continues to evolve over time. The knowledge in ontologies changes very rapidly that make the applications outdated if they continue to use old versions or unstable if they jump to new versions. Temporal frames using frame versioning and slot versioning are used to take care of dynamic nature of the ontologies. The paper proposes new tags and restructured OWL format enabling the applications to work with the old or new version of ontologies. Gene Ontology, a very dynamic ontology, has been used as a case study to explain the OWL Ontology with Temporal Tags.
Abstract: Clustering unstructured text documents is an
important issue in data mining community and has a number of
applications such as document archive filtering, document
organization and topic detection and subject tracing. In the real
world, some of the already clustered documents may not be of
importance while new documents of more significance may evolve.
Most of the work done so far in clustering unstructured text
documents overlooks this aspect of clustering. This paper, addresses
this issue by using the Fading Function. The unstructured text
documents are clustered. And for each cluster a statistics structure
called Cluster Profile (CP) is implemented. The cluster profile
incorporates the Fading Function. This Fading Function keeps an
account of the time-dependent importance of the cluster. The work
proposes a novel algorithm Clustering n-ary Merge Algorithm
(CnMA) for unstructured text documents, that uses Cluster Profile
and Fading Function. Experimental results illustrating the
effectiveness of the proposed technique are also included.
Abstract: EEG signal is one of the oldest measures of brain
activity that has been used vastly for clinical diagnoses and
biomedical researches. However, EEG signals are highly
contaminated with various artifacts, both from the subject and from
equipment interferences. Among these various kinds of artifacts,
ocular noise is the most important one. Since many applications such
as BCI require online and real-time processing of EEG signal, it is
ideal if the removal of artifacts is performed in an online fashion.
Recently, some methods for online ocular artifact removing have
been proposed. One of these methods is ARMAX modeling of EEG
signal. This method assumes that the recorded EEG signal is a
combination of EOG artifacts and the background EEG. Then the
background EEG is estimated via estimation of ARMAX parameters.
The other recently proposed method is based on adaptive filtering.
This method uses EOG signal as the reference input and subtracts
EOG artifacts from recorded EEG signals. In this paper we
investigate the efficiency of each method for removing of EOG
artifacts. A comparison is made between these two methods. Our
undertaken conclusion from this comparison is that adaptive filtering
method has better results compared with the results achieved by
ARMAX modeling.
Abstract: A lot of matching algorithms with different characteristics have been introduced in recent years. For real time systems these algorithms are usually based on minutiae features. In this paper we introduce a novel approach for feature extraction in which the extracted features are independent of shift and rotation of the fingerprint and at the meantime the matching operation is performed much more easily and with higher speed and accuracy. In this new approach first for any fingerprint a reference point and a reference orientation is determined and then based on this information features are converted into polar coordinates. Due to high speed and accuracy of this approach and small volume of extracted features and easily execution of matching operation this approach is the most appropriate for real time applications.