Abstract: This study is concerned with a new adaptive impedance control strategy to compensate for unknown time-varying environment stiffness and position. The uncertainties are expressed by Function Approximation Technique (FAT), which allows the update laws to be derived easily using Lyapunov stability theory. Computer simulation results are presented to validate the effectiveness of the proposed strategy.
Abstract: There is a acute water problem especially in the dry
season in and around Perundurai (Erode district, Tamil Nadu, India)
where there are more number of tannery units. Hence an attempt was
made to use the waste water from tannery industry for construction
purpose. The mechanical properties such as compressive strength,
tensile strength, flexural strength etc were studied by casting various
concrete specimens in form of cube, cylinders and beams etc and
were found to be satisfactory. Hence some special properties such as
chloride attack, sulphate attack and chemical attack are considered
and comparatively studied with the conventional potable water. In
this experimental study the results of specimens prepared by using
treated and untreated tannery effluent were compared with the
concrete specimens prepared by using potable water. It was observed
that the concrete had some reduction in strength while subjected to
chloride attack, sulphate attack and chemical attack. So admixtures
were selected and optimized in suitable proportion to counter act the
adverse effects and the results were found to be satisfactory.
Abstract: Recently, many existing partially blind signature scheme based on a single hard problem such as factoring, discrete logarithm, residuosity or elliptic curve discrete logarithm problems. However sooner or later these systems will become broken and vulnerable, if the factoring or discrete logarithms problems are cracked. This paper proposes a secured partially blind signature scheme based on factoring (FAC) problem and elliptic curve discrete logarithms (ECDL) problem. As the proposed scheme is focused on factoring and ECDLP hard problems, it has a solid structure and will totally leave the intruder bemused because it is very unlikely to solve the two hard problems simultaneously. In order to assess the security level of the proposed scheme a performance analysis has been conducted. Results have proved that the proposed scheme effectively deals with the partial blindness, randomization, unlinkability and unforgeability properties. Apart from this we have also investigated the computation cost of the proposed scheme. The new proposed scheme is robust and it is difficult for the malevolent attacks to break our scheme.
Abstract: In this research paper we have presented control
architecture for robotic arm movement and trajectory planning using
Fuzzy Logic (FL) and Genetic Algorithms (GAs). This architecture is
used to compensate the uncertainties like; movement, friction and
settling time in robotic arm movement. The genetic algorithms and
fuzzy logic is used to meet the objective of optimal control
movement of robotic arm. This proposed technique represents a
general model for redundant structures and may extend to other
structures. Results show optimal angular movement of joints as result
of evolutionary process. This technique has edge over the other
techniques as minimum mathematics complexity used.
Abstract: A scalable QoS aware multicast deployment in
DiffServ networks has become an important research dimension in
recent years. Although multicasting and differentiated services are
two complementary technologies, the integration of the two
technologies is a non-trivial task due to architectural conflicts
between them. A popular solution proposed is to extend the
functionality of the DiffServ components to support multicasting. In
this paper, we propose an algorithm to construct an efficient QoSdriven
multicast tree, taking into account the available bandwidth per
service class. We also present an efficient way to provision the
limited available bandwidth for supporting heterogeneous users. The
proposed mechanism is evaluated using simulated tests. The
simulated result reveals that our algorithm can effectively minimize
the bandwidth use and transmission cost
Abstract: Load forecasting has always been the essential part of
an efficient power system operation and planning. A novel approach
based on support vector machines is proposed in this paper for annual
power load forecasting. Different kernel functions are selected to
construct a combinatorial algorithm. The performance of the new
model is evaluated with a real-world dataset, and compared with two
neural networks and some traditional forecasting techniques. The
results show that the proposed method exhibits superior performance.
Abstract: This paper presents a new sensor-based online method for generating collision-free near-optimal paths for mobile robots pursuing a moving target amidst dynamic and static obstacles. At each iteration, first the set of all collision-free directions are calculated using velocity vectors of the robot relative to each obstacle and target, forming the Directive Circle (DC), which is a novel concept. Then, a direction close to the shortest path to the target is selected from feasible directions in DC. The DC prevents the robot from being trapped in deadlocks or local minima. It is assumed that the target's velocity is known, while the speeds of dynamic obstacles, as well as the locations of static obstacles, are to be calculated online. Extensive simulations and experimental results demonstrated the efficiency of the proposed method and its success in coping with complex environments and obstacles.
Abstract: Average current analysis checking the impact of
current flow is very important to guarantee the reliability of
semiconductor systems. As semiconductor process technologies
improve, the coupling capacitance often become bigger than self
capacitances. In this paper, we propose an analytic technique for
analyzing average current on interconnects in multi-conductor
structures. The proposed technique has shown to yield the acceptable
errors compared to HSPICE results while providing computational
efficiency.
Abstract: e-Government structures permits the government to operate in a more transparent and accountable manner of which it increases the power of the individual in relation to that of the government. This paper identifies the factors that determine customer-s attitude towards e-Government services using a theoretical model based on the Technology Acceptance Model. Data relating to the constructs were collected from 200 respondents. The research model was tested using Structural Equation Modeling (SEM) techniques via the Analysis of Moment Structure (AMOS 16) computer software. SEM is a comprehensive approach to testing hypotheses about relations among observed and latent variables. The proposed model fits the data well. The results demonstrated that e- Government services acceptance can be explained in terms of compatibility and attitude towards e-Government services. The setup of the e-Government services will be compatible with the way users work and are more likely to adopt e-Government services owing to their familiarity with the Internet for various official, personal, and recreational uses. In addition, managerial implications for government policy makers, government agencies, and system developers are also discussed.
Abstract: This paper presents a means for reducing the torque
variation during the revolution of a vertical-axis water turbine
(VAWaterT) by increasing the blade number. For this purpose, twodimensional
CFD analyses have been performed on a straight-bladed
Darrieus-type rotor. After describing the computational model and
the relative validation procedure, a complete campaign of
simulations, based on full RANS unsteady calculations, is proposed
for a three, four and five-bladed rotor architectures, characterized by
a NACA 0025 airfoil. For each proposed rotor configuration, flow
field characteristics are investigated at several values of tip speed
ratio, allowing a quantification of the influence of blade number on
flow geometric features and dynamic quantities, such as rotor torque
and power. Finally, torque and power curves are compared for the
three analyzed architectures, achieving a quantification of the effect
of blade number on overall rotor performance.
Abstract: This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA) and particle swarm optimization (PSO). Simulation results affirm that the proposed algorithm CRPSO, outperforms over its counterparts not only in terms of quality output i.e. sharpness at cut-off, pass band ripple, stop band ripple, and stop band attenuation but also in convergence speed with assured stability.
Abstract: This paper presents a technical speaker adaptation
method called WMLLR, which is based on maximum likelihood linear
regression (MLLR). In MLLR, a linear regression-based transform
which adapted the HMM mean vectors was calculated to maximize the
likelihood of adaptation data. In this paper, the prior knowledge of the
initial model is adequately incorporated into the adaptation. A series of
speaker adaptation experiments are carried out at a 30 famous city
names database to investigate the efficiency of the proposed method.
Experimental results show that the WMLLR method outperforms the
conventional MLLR method, especially when only few utterances
from a new speaker are available for adaptation.
Abstract: Following the loss of NASA's Space Shuttle
Columbia in 2003, it was determined that problems in the agency's
organization created an environment that led to the accident. One
component of the proposed solution resulted in the formation of the
NASA Engineering Network (NEN), a suite of information retrieval
and knowledge-sharing tools. This paper describes the
implementation of communities of practice, which are formed along
engineering disciplines. Communities of practice enable engineers to
leverage their knowledge and best practices to collaborate and take
information learning back to their jobs and embed it into the
procedures of the agency. This case study offers insight into using
traditional engineering disciplines for virtual collaboration, including
lessons learned during the creation and establishment of NASA-s
communities.
Abstract: Current image-based individual human recognition
methods, such as fingerprints, face, or iris biometric modalities
generally require a cooperative subject, views from certain aspects,
and physical contact or close proximity. These methods cannot
reliably recognize non-cooperating individuals at a distance in the
real world under changing environmental conditions. Gait, which
concerns recognizing individuals by the way they walk, is a relatively
new biometric without these disadvantages. The inherent gait
characteristic of an individual makes it irreplaceable and useful in
visual surveillance.
In this paper, an efficient gait recognition system for human
identification by extracting two features namely width vector of
the binary silhouette and the MPEG-7-based region-based shape
descriptors is proposed. In the proposed method, foreground objects
i.e., human and other moving objects are extracted by estimating
background information by a Gaussian Mixture Model (GMM) and
subsequently, median filtering operation is performed for removing
noises in the background subtracted image. A moving target classification
algorithm is used to separate human being (i.e., pedestrian)
from other foreground objects (viz., vehicles). Shape and boundary
information is used in the moving target classification algorithm.
Subsequently, width vector of the outer contour of binary silhouette
and the MPEG-7 Angular Radial Transform coefficients are taken as
the feature vector. Next, the Principal Component Analysis (PCA)
is applied to the selected feature vector to reduce its dimensionality.
These extracted feature vectors are used to train an Hidden Markov
Model (HMM) for identification of some individuals. The proposed
system is evaluated using some gait sequences and the experimental
results show the efficacy of the proposed algorithm.
Abstract: Freeways are originally designed to provide high
mobility to road users. However, the increase in population and
vehicle numbers has led to increasing congestions around the world.
Daily recurrent congestion substantially reduces the freeway capacity
when it is most needed. Building new highways and expanding the
existing ones is an expensive solution and impractical in many
situations. Intelligent and vision-based techniques can, however, be
efficient tools in monitoring highways and increasing the capacity of
the existing infrastructures. The crucial step for highway monitoring
is vehicle detection. In this paper, we propose one of such
techniques. The approach is based on artificial neural networks
(ANN) for vehicles detection and counting. The detection process
uses the freeway video images and starts by automatically extracting
the image background from the successive video frames. Once the
background is identified, subsequent frames are used to detect
moving objects through image subtraction. The result is segmented
using Sobel operator for edge detection. The ANN is, then, used in
the detection and counting phase. Applying this technique to the
busiest freeway in Riyadh (King Fahd Road) achieved higher than
98% detection accuracy despite the light intensity changes, the
occlusion situations, and shadows.
Abstract: Many difficulties are faced in the process of learning
computer programming. This paper will propose a system framework
intended to reduce cognitive load in learning programming. In first
section focus is given on the process of learning and the
shortcomings of the current approaches to learning programming.
Finally the proposed prototype is suggested along with the
justification of the prototype. In the proposed prototype the concept
map is used as visualization metaphor. Concept maps are similar to
the mental schema in long term memory and hence it can reduce
cognitive load well. In addition other method such as part code
method is also proposed in this framework to can reduce cognitive
load.
Abstract: Cancers could normally be marked by a number of
differentially expressed genes which show enormous potential as
biomarkers for a certain disease. Recent years, cancer classification
based on the investigation of gene expression profiles derived by
high-throughput microarrays has widely been used. The selection of
discriminative genes is, therefore, an essential preprocess step in
carcinogenesis studies. In this paper, we have proposed a novel gene
selector using information-theoretic measures for biological
discovery. This multivariate filter is a four-stage framework through
the analyses of feature relevance, feature interdependence, feature
redundancy-dependence and subset rankings, and having been
examined on the colon cancer data set. Our experimental result show
that the proposed method outperformed other information theorem
based filters in all aspect of classification errors and classification
performance.
Abstract: In this study, active tendons with Proportional Integral
Derivation type controllers were applied to a SDOF and a MDOF
building model. Physical models of buildings were constituted with
virtual springs, dampers and rigid masses. After that, equations of
motion of all degrees of freedoms were obtained. Matlab Simulink
was utilized to obtain the block diagrams for these equations of
motion. Parameters for controller actions were found by using a trial
method. After earthquake acceleration data were applied to the
systems, building characteristics such as displacements, velocities,
accelerations and transfer functions were analyzed for all degrees of
freedoms. Comparisons on displacement vs. time, velocity vs. time,
acceleration vs. time and transfer function (Db) vs. frequency (Hz)
were made for uncontrolled and controlled buildings. The results
show that the method seems feasible.
Abstract: Current research has explored the impact of
instructional immediacy, defined as those behaviors that help build
close relationships or feelings of closeness, both on cognition and
motivation in the traditional classroom and online classroom;
however, online courses continue to suffer from higher dropout rates.
Based on Albert Bandura-s Social Cognitive Theory, four primary
relationships or interactions in an online course will be explored in
light of how they can provide immediacy thereby reducing student
attrition and improving cognitive learning. The four relationships are
teacher-student, student-student, and student-content, and studentcomputer.
Results of a study conducted with inservice teachers
completing a 14-week online professional development technology
course will be examined to demonstrate immediacy strategies that
improve cognitive learning and reduce student attrition. Results of
the study reveal that students can be motivated through various
interactions and instructional immediacy behaviors which lead to
higher completion rates, improved self-efficacy, and cognitive
learning.
Abstract: The number of framework conceived for e-learning
constantly increase, unfortunately the creators of learning materials
and educational institutions engaged in e-formation adopt a
“proprietor" approach, where the developed products (courses,
activities, exercises, etc.) can be exploited only in the framework
where they were conceived, their uses in the other learning
environments requires a greedy adaptation in terms of time and
effort. Each one proposes courses whose organization, contents,
modes of interaction and presentations are unique for all learners,
unfortunately the latter are heterogeneous and are not interested by
the same information, but only by services or documents adapted to
their needs. Currently the new tendency for the framework
conceived for e-learning, is the interoperability of learning materials,
several standards exist (DCMI (Dublin Core Metadata Initiative)[2],
LOM (Learning Objects Meta data)[1], SCORM (Shareable Content
Object Reference Model)[6][7][8], ARIADNE (Alliance of Remote
Instructional Authoring and Distribution Networks for Europe)[9],
CANCORE (Canadian Core Learning Resource Metadata
Application Profiles)[3]), they converge all to the idea of learning
objects. They are also interested in the adaptation of the learning
materials according to the learners- profile. This article proposes an
approach for the composition of courses adapted to the various
profiles (knowledge, preferences, objectives) of learners, based on
two ontologies (domain to teach and educational) and the learning
objects.