Abstract: In this paper as showed a non-invasive 3D eye tracker
for optometry clinical applications. Measurements of biomechanical
variables in clinical practice have many font of errors associated with
traditional procedments such cover test (CT), near point of
accommodation (NPC), eye ductions (ED), eye vergences (EG) and,
eye versions (ES). Ocular motility should always be tested but all
evaluations have a subjective interpretations by practitioners, the
results is based in clinical experiences, repeatability and accuracy
don-t exist. Optometric-lab is a tool with 3 (tree) analogical video
cameras triggered and synchronized in one acquisition board AD.
The variables globe rotation angle and velocity can be quantified.
Data record frequency was performed with 27Hz, camera calibration
was performed in a know volume and image radial distortion
adjustments.
Abstract: Green Roofs offers numerous advantages, including lowering ambient temperature, which is of increasing interest due to global warming concerns. However, there are technical problems pertaining to waterproofing to be resolved. Currently, the only recognized green roof waterproofing test is the German standard FLL. This paper examines the potential of replicating the test in tropical climate and reducing the test duration by using pre-grown plants. A three year old sample and a new setup were used for this experimental study. The new setup was prepared with close reference to the FLL standards and was compared against the three year old sample. Results showed that the waterproofing membrane was damaged by plant roots in both setups. Joints integrity was also challenged.
Abstract: Industrial robots play a vital role in automation
however only little effort are taken for the application of robots in
machining work such as Grinding, Cutting, Milling, Drilling,
Polishing etc. Robot parallel manipulators have high stiffness,
rigidity and accuracy, which cannot be provided by conventional
serial robot manipulators. The aim of this paper is to perform the
modeling and the workspace analysis of a 3 DOF Parallel
Manipulator (3 DOF PM). The 3 DOF PM was modeled and
simulated using 'ADAMS'. The concept involved is based on the
transformation of motion from a screw joint to a spherical joint
through a connecting link. This paper work has been planned to
model the Parallel Manipulator (PM) using screw joints for very
accurate positioning. A workspace analysis has been done for the
determination of work volume of the 3 DOF PM. The position of the
spherical joints connected to the moving platform and the
circumferential points of the moving platform were considered for
finding the workspace. After the simulation, the position of the joints
of the moving platform was noted with respect to simulation time and
these points were given as input to the 'MATLAB' for getting the
work envelope. Then 'AUTOCAD' is used for determining the work
volume. The obtained values were compared with analytical
approach by using Pappus-Guldinus Theorem. The analysis had been
dealt by considering the parameters, link length and radius of the
moving platform. From the results it is found that the radius of
moving platform is directly proportional to the work volume for a
constant link length and the link length is also directly proportional
to the work volume, at a constant radius of the moving platform.
Abstract: The development of wearable sensing technologies is a great challenge which is being addressed by the Proetex FP6 project (www.proetex.org). Its main aim is the development of wearable sensors to improve the safety and efficiency of emergency personnel. This will be achieved by continuous, real-time monitoring of vital signs, posture, activity, and external hazards surrounding emergency workers. We report here the development of carbon dioxide (CO2) sensing boot by incorporating commercially available CO2 sensor with a wireless platform into the boot assembly. Carefully selected commercially available sensors have been tested. Some of the key characteristics of the selected sensors are high selectivity and sensitivity, robustness and the power demand. This paper discusses some of the results of CO2 sensor tests and sensor integration with wireless data transmission
Abstract: Optimum communication and performance in
Wireless Sensor Networks, constitute multi-facet challenges due to
the specific networking characteristics as well as the scarce resource
availability. Furthermore, it is becoming increasingly apparent that
isolated layer based approaches often do not meet the demands posed
by WSNs applications due to omission of critical inter-layer
interactions and dependencies. As a counterpart, cross-layer is
receiving high interest aiming to exploit these interactions and
increase network performance. However, in order to clearly identify
existing dependencies, comprehensive performance studies are
required evaluating the effect of different critical network parameters
on system level performance and behavior.This paper-s main
objective is to address the need for multi-parametric performance
evaluations considering critical network parameters using a well
known network simulator, offering useful and practical conclusions
and guidelines. The results reveal strong dependencies among
considered parameters which can be utilized by and drive future
research efforts, towards designing and implementing highly efficient
protocols and architectures.
Abstract: This paper proposes a low-voltage and low-power
fully integrated digitally tuned continuous-time channel selection
filter for WiMAX applications. A 5th-order elliptic low-pass filter is
realized in a Gm-C topology. The bandwidth of the fully differential
filter is reconfigurable from 2.5MHz to 20MHz (8x) for different
requirements in WiMAX applications. The filter is simulated in a
standard 90nm CMOS process. Simulation results show the THD
(@Vout =100mVpp) is less than -66dB. The in-band ripple of the
filter is about 0.15dB. The filter consumes 1.5mW from a supply
voltage of 0.9V.
Abstract: In the context of large volume Big Divisor (nearly)
SLagy D3/D7 μ-Split SUSY [1], after an explicit identification
of first generation of SM leptons and quarks with fermionic superpartners
of four Wilson line moduli, we discuss the identification of
gravitino as a potential dark matter candidate by explicitly calculating
the decay life times of gravitino (LSP) to be greater than age of
universe and lifetimes of decays of the co-NLSPs (the first generation
squark/slepton and a neutralino) to the LSP (the gravitino) to be
very small to respect BBN constraints. Interested in non-thermal
production mechanism of gravitino, we evaluate the relic abundance
of gravitino LSP in terms of that of the co-NLSP-s by evaluating
their (co-)annihilation cross sections and hence show that the former
satisfies the requirement for a potential Dark Matter candidate. We
also show that it is possible to obtain a 125 GeV light Higgs in our
setup.
Abstract: For decades, the defense business has been plagued by
not having a reliable, deterministic method to know when the Kalman
filter solution for passive ranging application is reliable for use by the
fighter pilot. This has made it hard to accurately assess when the
ranging solution can be used for situation awareness and weapons
use. To date, we have used ad hoc rules-of-thumb to assess when we
think the estimate of the Kalman filter standard deviation on range is
reliable. A reliable algorithm has been developed at BAE Systems
Electronics & Integrated Solutions that monitors the Kalman gain
matrix elements – and a patent is pending. The “settling" of the gain
matrix elements relates directly to when we can assess the time when
the passive ranging solution is within the 10 percent-of-truth value.
The focus of the paper is on surface-based passive ranging – but the
method is applicable to airborne targets as well.
Abstract: Artificial Immune System (AIS) is relatively naive paradigm for intelligent computations. The inspiration for AIS is derived from natural Immune System (IS). Classically it is believed that IS strives to discriminate between self and non-self. Most of the existing AIS research is based on this approach. Danger Theory (DT) argues this approach and proposes that IS fights against danger producing elements and tolerates others. We, the computational researchers, are not concerned with the arguments among immunologists but try to extract from it novel abstractions for intelligent computation. This paper aims to follow DT inspiration for intelligent data processing. The approach may introduce new avenue in intelligent processing. The data used is system calls data that is potentially significant in intrusion detection applications.
Abstract: DC-DC converters are widely used in regulated switched mode power supplies and in DC motor drive applications. There are several sources of unwanted nonlinearity in practical power converters. In addition, their operation is characterized by switching that gives birth to a variety of nonlinear dynamics. DC-DC buck and boost converters controlled by pulse-width modulation (PWM) have been simulated. The voltage waveforms and attractors obtained from the circuit simulation have been studied. With the onset of instability, the phenomenon of subharmonic oscillations, quasi-periodicity, bifurcations, and chaos have been observed. This paper is mainly motivated by potential contributions of chaos theory in the design, analysis and control of power converters, in particular and power electronics circuits, in general.
Abstract: The dynamics of the Autonomous Underwater
Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate
accurately because of the variations of these coefficients with
different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain
the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line
adaptive fuzzy model and adaptive neural fuzzy network (ANFN)
model techniques to overcome the uncertain external disturbance and
the difficulties of modelling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The models- parameters are adapted according
to the back propagation algorithm based upon the error between the
identified model and the actual output of the plant. The proposed
ANFN model adopts a functional link neural network (FLNN) as the
consequent part of the fuzzy rules. Thus, the consequent part of the
ANFN model is a nonlinear combination of input variables. Fuzzy
control system is applied to guide and control the AUV using both
adaptive models and mathematical model. Simulation results show
the superiority of the proposed adaptive neural fuzzy network
(ANFN) model in tracking of the behavior of the AUV accurately
even in the presence of noise and disturbance.
Abstract: This paper presents an adaptive nonlinear position
controller with velocity constraint, capable of combining the
input-output linearization technique and Lyapunov stability theory.
Based on the Lyapunov stability theory, the adaptation law of the
proposed controller is derived along with the verification of the overall
system-s stability. Computer simulation results demonstrate that the
proposed controller is robust and it can ensure transient stability of
BLDCM, under the occurrence of a large sudden fault.
Abstract: An application framework provides a reusable design
and implementation for a family of software systems. Application
developers extend the framework to build their particular
applications using hooks. Hooks are the places identified to show
how to use and customize the framework. Hooks define Framework
Interface Classes (FICs) and their possible specifications, which
helps in building reusable test cases for the implementations of these
classes. In applications developed using gray-box frameworks, FICs
inherit framework classes or use them without inheritance. In this
paper, a test-case generation technique is extended to build test cases
for FICs built for gray-box frameworks. A tool is developed to
automate the introduced technique.
Abstract: Ranking of fuzzy numbers play an important role in
decision making, optimization, forecasting etc. Fuzzy numbers must
be ranked before an action is taken by a decision maker. In this
paper, with the help of several counter examples it is proved that
ranking method proposed by Chen and Chen (Expert Systems with
Applications 36 (2009) 6833-6842) is incorrect. The main aim of this
paper is to propose a new approach for the ranking of generalized
trapezoidal fuzzy numbers. The main advantage of the proposed
approach is that the proposed approach provide the correct ordering
of generalized and normal trapezoidal fuzzy numbers and also the
proposed approach is very simple and easy to apply in the real life
problems. It is shown that proposed ranking function satisfies all
the reasonable properties of fuzzy quantities proposed by Wang and
Kerre (Fuzzy Sets and Systems 118 (2001) 375-385).
Abstract: This paper presented a collaborative education model,
which consists four parts: collaborative teaching, collaborative
working, collaborative training and interaction. Supported by an
e-learning platform, collaborative education was practiced in a data
structure e-learning course. Data collected shows that most of students
accept collaborative education. This paper goes one step attempting to
determine which aspects appear to be most important or helpful in
collaborative education.
Abstract: In rotating machinery one of the critical components
that is prone to premature failure is the rolling bearing.
Consequently, early warning of an imminent bearing failure is much
critical to the safety and reliability of any high speed rotating
machines. This study is concerned with the application of Recurrence
Quantification Analysis (RQA) in fault detection of rolling element
bearings in rotating machinery. Based on the results from this study it
is reported that the RQA variable, percent determinism, is sensitive
to the type of fault investigated and therefore can provide useful
information on bearing damage in rolling element bearings.
Abstract: The availability of broadband internet and increased
access to computers has been instrumental in the rise of internet
literacy in Malaysia. This development has led to the adoption of
online shopping by many Malaysians. On another note, the
Government has supported the development and production of local
herbal products. This has resulted in an increase in the production and
diversity of products by SMEs. The purpose of this study is to
evaluate the influence of the Malaysian demographic factors and
selected attitudinal characteristics in relation to the online purchasing
of herbal products. In total, 1054 internet users were interviewed
online and Chi-square analysis was used to determine the relationship
between demographic variables and different aspects of online
shopping for herbal products. The overall results show that the
demographic variables such as age, gender, education level, income
and ethnicity were significant when considering the online shopping
antecedents of trust, quality of herbal products, perceived risks and
perceived benefits.
Abstract: In sport, human resources management gives special
attention to method of applying volunteers, their maintenance, and
participation of volunteers with each other and management
approaches for better operation of events celebrants. The recognition
of volunteers- characteristics and motives is important to notice,
because it makes the basis of their participation and commitment at
sport environment. The motivation and commitment of 281
volunteers were assessed using the organizational commitment scale,
motivation scale and personal characteristics questionnaire.The
descriptive results showed that; 64% of volunteers were women with
age average 21/24 years old. They were physical education student,
single (71/9%), without occupation (53%) and with average of 5
years sport experience. Their most important motivation was career
factor and the most important commitment factor was normative
factor. The results of examining the hypothesized showed that; age,
sport experience and education are effective in the amount of
volunteers- commitment. And the motive factors such as career,
material, purposive and protective factors also have the power to
predict the amount of sports volunteers- commitment value.
Therefore it is recommended to provide possible opportunities for
volunteers and carrying out appropriate instructional courses by
events executive managers.
Abstract: Aquatic and semi aquatic birds as a group are suited to
feed and breed in environments in which water forms a fundamental
part. These birds are biological indicator in aquatic environment,
because these birds belong to the top level of food chain in aquatic
ecosystems. There are 61 species in 14 families of aquatic and semi
aquatic birds in Iran. The birds of the Sattarkhan Lake belong to 16
species in 8 families which include 26.2 percent of total Aquatic and
semi aquatic bird species and 57% of Aquatic and semi aquatic bird's
family of Iran. Study was carried out monthly at Sattarkhan Lake
show the existence of Phalacrocorax carbo, Ardea cinerea, Egretta
alba, Egretta garzetta, Bubulcus ibis, Botaurus stellaris, Sterna
hirundo, Chlidonias leucopterus, Larus minutus, Larus argentatus,
Larus ridibunbus, Alcedo atthis, Ciconia ciconia, Plegadis
falcinellus, Circus aeruginosus, Corvus frugilegus
Abstract: Purpose: To explore the use of Curvelet transform to
extract texture features of pulmonary nodules in CT image and support
vector machine to establish prediction model of small solitary
pulmonary nodules in order to promote the ratio of detection and
diagnosis of early-stage lung cancer. Methods: 2461 benign or
malignant small solitary pulmonary nodules in CT image from 129
patients were collected. Fourteen Curvelet transform textural features
were as parameters to establish support vector machine prediction
model. Results: Compared with other methods, using 252 texture
features as parameters to establish prediction model is more proper.
And the classification consistency, sensitivity and specificity for the
model are 81.5%, 93.8% and 38.0% respectively. Conclusion: Based
on texture features extracted from Curvelet transform, support vector
machine prediction model is sensitive to lung cancer, which can
promote the rate of diagnosis for early-stage lung cancer to some
extent.