Abstract: In this paper we promote the Ultra Low Voltage (ULV) NAND gate to replace either partly or entirely the encryption block of a design to withstand power analysis attack.
Abstract: The importance of good requirements engineering is well documented. Agile practices, promoting collaboration and communications, facilitate the elicitation and management of volatile requirements. However, current Agile practices work in a well-defined environment. It is necessary to have a co-located customer. With distributed development it is not always possible to realize this co-location. In this environment a suitable process, possibly supported by tools, is required to support changing requirements. This paper introduces the issues of concern when managing requirements in a distributed environment and describes work done at the Software Technology Research Centre as part of the NOMAD project.
Abstract: Recent developments in Soft computing techniques,
power electronic switches and low-cost computational hardware have
made it possible to design and implement sophisticated control
strategies for sensorless speed control of AC motor drives. Such an
attempt has been made in this work, for Sensorless Speed Control of
Induction Motor (IM) by means of Direct Torque Fuzzy Control
(DTFC), PI-type fuzzy speed regulator and MRAS speed estimator
strategy, which is absolutely nonlinear in its nature. Direct torque
control is known to produce quick and robust response in AC drive
system. However, during steady state, torque, flux and current ripple
occurs. So, the performance of conventional DTC with PI speed
regulator can be improved by implementing fuzzy logic techniques.
Certain important issues in design including the space vector
modulated (SVM) 3-Ф voltage source inverter, DTFC design,
generation of reference torque using PI-type fuzzy speed regulator
and sensor less speed estimator have been resolved. The proposed
scheme is validated through extensive numerical simulations on
MATLAB. The simulated results indicate the sensor less speed
control of IM with DTFC and PI-type fuzzy speed regulator provides
satisfactory high dynamic and static performance compare to
conventional DTC with PI speed regulator.
Abstract: This paper presents modeling and analysis of 12-phase distribution static compensator (DSTATCOM), which is capable of balancing the source currents in spite of unbalanced loading and phase outages. In addition to balance the supply current, the power factor can be set to a desired value. The theory of instantaneous symmetrical components is used to generate the twelve-phase reference currents. These reference currents are then tracked using current controlled voltage source inverter, operated in a hysteresis band control scheme. An ideal compensator in place of physical realization of the compensator is used. The performance of the proposed DTATCOM is validated through MATLAB simulation and detailed simulation results are given.
Abstract: Stream Control Transmission Protocol (SCTP) has been
proposed to provide reliable transport of real-time communications.
Due to its attractive features, such as multi-streaming and multihoming,
the SCTP is often expected to be an alternative protocol
for TCP and UDP. In the original SCTP standard, the secondary path
is mainly regarded as a redundancy. Recently, most of researches
have focused on extending the SCTP to enable a host to send its
packets to a destination over multiple paths simultaneously. In order
to transfer packets concurrently over the multiple paths, the SCTP
should be well designed to avoid unnecessary fast retransmission
and the mis-estimation of congestion window size through the paths.
Therefore, we propose an Enhanced Cooperative ACK SCTP (ECASCTP)
to improve the path recovery efficiency of multi-homed host
which is under concurrent multiple transfer mode. We evaluated the
performance of our proposed scheme using ns-2 simulation in terms
of cwnd variation, path recovery time, and goodput. Our scheme
provides better performance in lossy and path asymmetric networks.
Abstract: To determine the length of engagement threads of a bolt installed in a tapped part in order to avoid the threads stripping remains a very current problem in the design of the thread assemblies. It does not exist a calculation method formalized for the cases where the bolt is screwed directly in a ductile material. In this article, we study the behavior of the threads stripping of a loaded assembly by using a modelling by finite elements and a rupture criterion by damage. This modelling enables us to study the different parameters likely to influence the behavior of this bolted connection. We study in particular, the influence of couple of materials constituting the connection, of the bolt-s diameter and the geometrical characteristics of the tapped part, like the external diameter and the length of engagement threads. We established an experiments design to know the most significant parameters. That enables us to propose a simple expression making possible to calculate the resistance of the threads whatever the metallic materials of the bolt and the tapped part. We carried out stripping tests in order to validate our model. The estimated results are very close to those obtained by the tests.
Abstract: Wind energy has been shown to be one of the most
viable sources of renewable energy. With current technology, the low
cost of wind energy is competitive with more conventional sources of
energy such as coal. Most blades available for commercial grade
wind turbines incorporate a straight span-wise profile and airfoil
shaped cross sections. These blades are found to be very efficient at
lower wind speeds in comparison to the potential energy that can be
extracted. However as the oncoming wind speed increases the
efficiency of the blades decreases as they approach a stall point. This
paper explores the possibility of increasing the efficiency of the
blades at higher wind speeds while maintaining efficiency at the
lower wind speeds. The design intends to maintain efficiency at
lower wind speeds by selecting the appropriate orientation and size
of the airfoil cross sections based on a low oncoming wind speed and
given constant rotation rate. The blades will be made more efficient
at higher wind speeds by implementing a swept blade profile.
Performance was investigated using the computational fluid
dynamics (CFD).
Abstract: Detecting protein-protein interactions is a central problem in computational biology and aberrant such interactions may have implicated in a number of neurological disorders. As a result, the prediction of protein-protein interactions has recently received considerable attention from biologist around the globe. Computational tools that are capable of effectively identifying protein-protein interactions are much needed. In this paper, we propose a method to detect protein-protein interaction based on substring similarity measure. Two protein sequences may interact by the mean of the similarities of the substrings they contain. When applied on the currently available protein-protein interaction data for the yeast Saccharomyces cerevisiae, the proposed method delivered reasonable improvement over the existing ones.
Abstract: The scale, complexity and worldwide geographical
spread of the LHC computing and data analysis problems are
unprecedented in scientific research. The complexity of processing
and accessing this data is increased substantially by the size and
global span of the major experiments, combined with the limited
wide area network bandwidth available. We present the latest
generation of the MONARC (MOdels of Networked Analysis at
Regional Centers) simulation framework, as a design and modeling
tool for large scale distributed systems applied to HEP experiments.
We present simulation experiments designed to evaluate the
capabilities of the current real-world distributed infrastructure to
support existing physics analysis processes and the means by which
the experiments bands together to meet the technical challenges
posed by the storage, access and computing requirements of LHC
data analysis within the CMS experiment.
Abstract: In this paper, a neural tree (NT) classifier having a
simple perceptron at each node is considered. A new concept for
making a balanced tree is applied in the learning algorithm of the
tree. At each node, if the perceptron classification is not accurate and
unbalanced, then it is replaced by a new perceptron. This separates
the training set in such a way that almost the equal number of patterns
fall into each of the classes. Moreover, each perceptron is trained only
for the classes which are present at respective node and ignore other
classes. Splitting nodes are employed into the neural tree architecture
to divide the training set when the current perceptron node repeats
the same classification of the parent node. A new error function based
on the depth of the tree is introduced to reduce the computational
time for the training of a perceptron. Experiments are performed to
check the efficiency and encouraging results are obtained in terms of
accuracy and computational costs.
Abstract: Horseradish (Armoracia rusticana) is a perennial herb belonging to the Brassicaceae family and contains biologically active substances. The aim of the current research was to determine best method for extraction of phenolic compounds from horseradish roots showing high antiradical activity. Three genotypes (No. 105; No. 106 and variety ‘Turku’) of horseradish roots were extracted with eight different solvents: n-hexane, ethyl acetate, diethyl ether, 2-propanol, acetone, ethanol (95%), ethanol / water / acetic acid (80/20/1 v/v/v) and ethanol / water (80/20 by volume) using two extraction methods (conventional and Soxhlet). As the best solvents ethanol and ethanol / water solutions can be chosen. Although in Soxhlet extracts TPC was higher, scavenging activity of DPPH˙ radicals did not increase. It can be concluded that using Soxhlet extraction method more compounds that are not effective antioxidants.
Abstract: Current OCR technology does not allow to
accurately recognizing small text images, such as those found
in web images. Our goal is to investigate new approaches to
recognize very low resolution text images containing antialiased
character shapes.
This paper presents a preliminary study on the variability of
such characters and the feasibility to discriminate them by
using geometrical features. In a first stage we analyze the
distribution of these features. In a second stage we present a
study on the discriminative power for recognizing isolated
characters, using various rendering methods and font
properties. Finally we present interesting results of our
evaluation tests leading to our conclusion and future focus.
Abstract: Describes the current situation of educational Robotics
"the State of the art" its concept, its evolution their niches of
opportunity, academic and business and the importance of education
and academic outreach. It shows that the development of high-tech
automated educational materials influence the teaching-learning
process and that communication between machines and humans is a
reality.
Abstract: Current research on semantic web aims at making intelligent web pages meaningful for machines. In this way, ontology plays a primary role. We believe that logic can help ontology languages (such as OWL) to be more fluent and efficient. In this paper we try to combine logic with OWL to reduce some disadvantages of this language. Therefore we extend OWL by logic and also show how logic can satisfy our future expectations of an ontology language.
Abstract: Rapid advancement in computing technology brings
computers and humans to be seamlessly integrated in future. The
emergence of smartphone has driven computing era towards
ubiquitous and pervasive computing. Recognizing human activity has
garnered a lot of interest and has raised significant researches-
concerns in identifying contextual information useful to human
activity recognition. Not only unobtrusive to users in daily life,
smartphone has embedded built-in sensors that capable to sense
contextual information of its users supported with wide range
capability of network connections. In this paper, we will discuss the
classification algorithms used in smartphone-based human activity.
Existing technologies pertaining to smartphone-based researches in
human activity recognition will be highlighted and discussed. Our
paper will also present our findings and opinions to formulate
improvement ideas in current researches- trends. Understanding
research trends will enable researchers to have clearer research
direction and common vision on latest smartphone-based human
activity recognition area.
Abstract: Tensile armour wires provide a flexible pipe's
resistance to longitudinal stresses. Flexible pipe manufacturers need
to know the effect of defects such as scratches and cracks, with
dimensions less than 0.2mm which is the limit of the current nondestructive
detection technology, on the fracture stress and fracture
strain of the wire for quality assurance purposes. Recent research
involving the determination of the fracture strength of cracked wires
employed laboratory testing and classical fracture mechanics
approach using non-standardised fracture mechanics specimens
because standard test specimens could not be manufactured from the
wires owing to their sizes. In this work, the effect of miniature
cracks on the fracture properties of tensile armour wires was
investigated using laboratory and finite element tensile testing
simulations with the phenomenological shear fracture model. The
investigation revealed that the presence of cracks shallower than
0.2mm is worse on the fracture strain of the wire.
Abstract: This paper presents the applicability of artificial
neural networks for 24 hour ahead solar power generation forecasting
of a 20 kW photovoltaic system, the developed forecasting is suitable
for a reliable Microgrid energy management. In total four neural
networks were proposed, namely: multi-layred perceptron, radial
basis function, recurrent and a neural network ensemble consisting in
ensemble of bagged networks. Forecasting reliability of the proposed
neural networks was carried out in terms forecasting error
performance basing on statistical and graphical methods. The
experimental results showed that all the proposed networks achieved
an acceptable forecasting accuracy. In term of comparison the neural
network ensemble gives the highest precision forecasting comparing
to the conventional networks. In fact, each network of the ensemble
over-fits to some extent and leads to a diversity which enhances the
noise tolerance and the forecasting generalization performance
comparing to the conventional networks.
Abstract: This paper fist examines three set of bivariate cointegrations between any two of current accounts, stock markets, and currency exchange markets in ten Asian countries. Furthermore, we examined the effect of country characters on this bivariate cointegration. Our findings suggest that for three sets of cointegration test, each sample country at least exists one cointegration. India consistently exhibited a bi-directional causal relationship between any two of three indicators. Unlike Pan et al. (2007) and Phylaktis and Ravazzolo (2005), we found that such cointegration is influenced by three characteristics: capital control; flexibility in foreign exchange rates; and the ratio of trade to GDP. These characteristics are the result of liberalization in each Asian country. This implies that liberalization policies are effective on improving the cointegration between any two of financial markets and current account for ten Asian countries.
Abstract: In this paper, a new approach for design of a fully
differential second order current mode continuous-time sigma-delta
modulator is presented. For circuit implementation, square root
domain (SRD) translinear loop based on floating-gate MOS
transistors that operate in saturation region is employed. The
modulator features, low supply voltage, low power consumption
(8mW) and high dynamic range (55dB). Simulation results confirm
that this design is suitable for data converters.
Abstract: Detection of squirrel cage induction motor (SCIM) broken bars has long been an important but difficult job in the detection area of motor faults. Early detection of this abnormality in the motor would help to avoid costly breakdowns. A new detection method based on particle swarm optimization (PSO) is presented in this paper. Stator current in an induction motor will be measured and characteristic frequency components of faylted rotor will be detected by minimizing a fitness function using pso. Supply frequency and side band frequencies and their amplitudes can be estimated by the proposed method. The proposed method is applied to a faulty motor with one and two broken bars in different loading condition. Experimental results prove that the proposed method is effective and applicable.