Abstract: Power transformer consists of components which are
under consistent thermal and electrical stresses. The major
component which degrades under these stresses is the paper
insulation of the power transformer. At site, lightning impulses and
cable faults may cause the winding deformation. In addition, the
winding may deform due to impact during transportation. A
deformed winding will excite more stress to its insulating paper thus
will degrade it. Insulation degradation will shorten the life-span of
the transformer. Currently there are two methods of detecting the
winding deformation which are Sweep Frequency Response
Analysis (SFRA) and Low Voltage Impulse Test (LVI). The latter
injects current pulses to the winding and capture the admittance
plot. In this paper, a transformer which experienced overheating and
arcing was identified, and both SFRA and LVI were performed.
Next, the transformer was brought to the factory for untanking. The
untanking results revealed that the LVI is more accurate than the
SFRA method for this case study.
Abstract: Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.
Abstract: The objective of this research is to develop the
performance indicators (PIs) in operational level for the Pre-hospital Emergency Medical Service (EMS) system employing in Thailand. This research started with ascertaining the current pre-hospital care
system. The team analyzed the strategies of Narerthorn, a government unit under the ministry of public health, and the existing PIs of the pre-hospital care. Afterwards, the current National Strategic Plan of EMS development (2008-2012) of the Emergency
Medical Institute of Thailand (EMIT) was considered using strategic
analysis to developed Strategy Map (SM) and identified the Success
Factors (SFs). The analysis results from strategy map and SFs were used to develop the Performance Indicators (PIs). To verify the set of
PIs, the team has interviewed with the relevant practitioners for the possibilities to implement the PIs. To this paper, it was to ascertain
that all the developed PIs support the objectives of the strategic plan. Nevertheless, the results showed that the operational level PIs suited
only with the first dimension of National Strategic Plan
(infrastructure and information technology development). Besides,
the SF was the infrastructure development (to contribute the EMS system to people throughout with standard and efficiency both in normally and disaster conditions). Finally, twenty-nine indicators
were developed from the analysis results of SM and SFs.
Abstract: The soil moisture content is an important property of
the soil. The results of mean weekly gravimetric soil moisture
content, measured for the three soil layers within the A horizon,
showed that it was higher for the top 5 cm over the whole period of
monitoring (15/7/2004 up to 10/11/05) with the variation becoming
greater during winter time. This reflects the pattern of rainfall in
Ireland which is spread over the whole year and shows that light
rainfall events during summer time were compensated by loss
through evapotranspiration, but only in the top 5 cm of soil. This
layer had the highest porosity and highest moisture holding capacity
due to the high content of organic matter. The gravimetric soil
moisture contents of the top 5 cm and the underlying 5-15 and 15-25
cm layers show that bottom site of the Hill Field had higher soil
moisture content than the middle and top sites during the whole
period of monitoring.
Abstract: The objective of this paper is to study the electrical
resistivity complexity between field and laboratory measurement, in
order to improve the effectiveness of data interpretation for
geophysical ground resistivity survey. The geological outcrop in
Penang, Malaysia with an obvious layering contact was chosen as the
study site. Two dimensional geoelectrical resistivity imaging were
used in this study to maps the resistivity distribution of subsurface,
whereas few subsurface sample were obtained for laboratory
advance. In this study, resistivity of samples in original conditions is
measured in laboratory by using time domain low-voltage technique,
particularly for granite core sample and soil resistivity measuring set
for soil sample. The experimentation results from both schemes are
studied, analyzed, calibrated and verified, including basis and
correlation, degree of tolerance and characteristics of substance.
Consequently, the significant different between both schemes is
explained comprehensively within this paper.
Abstract: In this paper, transversal vibration of buried pipelines
during loading induced by underground explosions is analyzed. The
pipeline is modeled as an infinite beam on an elastic foundation, so
that soil-structure interaction is considered by means of transverse
linear springs along the pipeline. The pipeline behavior is assumed to
be ideal elasto-plastic which an ultimate strain value limits the plastic
behavior. The blast loading is considered as a point load, considering
the affected length at some point of the pipeline, in which the
magnitude decreases exponentially with time. A closed-form solution
for the quasi-static problem is carried out for both elastic and elasticperfect
plastic behaviors of pipe materials. At the end, a comparative
study on steel and polyethylene pipes with different sizes buried in
various soil conditions, affected by a predefined underground
explosion is conducted, in which effect of each parameter is
discussed.
Abstract: The issue of unintentional islanding in PV grid
interconnection still remains as a challenge in grid-connected
photovoltaic (PV) systems. This paper discusses the overview of
popularly used anti-islanding detection methods, practically applied
in PV grid-connected systems. Anti-islanding methods generally can
be classified into four major groups, which include passive methods,
active methods, hybrid methods and communication base methods.
Active methods have been the preferred detection technique over the
years due to very small non-detected zone (NDZ) in small scale
distribution generation. Passive method is comparatively simpler
than active method in terms of circuitry and operations. However, it
suffers from large NDZ that significantly reduces its performance.
Communication base methods inherit the advantages of active and
passive methods with reduced drawbacks. Hybrid method which
evolved from the combination of both active and passive methods
has been proven to achieve accurate anti-islanding detection by many
researchers. For each of the studied anti-islanding methods, the
operation analysis is described while the advantages and
disadvantages are compared and discussed. It is difficult to pinpoint a
generic method for a specific application, because most of the
methods discussed are governed by the nature of application and
system dependent elements. This study concludes that the setup and
operation cost is the vital factor for anti-islanding method selection in
order to achieve minimal compromising between cost and system
quality.
Abstract: The objective of this paper is to estimate realistic
principal extrusion process parameters by means of artificial neural
network. Conventionally, finite element analysis is used to derive
process parameters. However, the finite element analysis of the
extrusion model does not consider the manufacturing process
constraints in its modeling. Therefore, the process parameters
obtained through such an analysis remains highly theoretical.
Alternatively, process development in industrial extrusion is to a
great extent based on trial and error and often involves full-size
experiments, which are both expensive and time-consuming. The
artificial neural network-based estimation of the extrusion process
parameters prior to plant execution helps to make the actual extrusion
operation more efficient because more realistic parameters may be
obtained. And so, it bridges the gap between simulation and real
manufacturing execution system. In this work, a suitable neural
network is designed which is trained using an appropriate learning
algorithm. The network so trained is used to predict the
manufacturing process parameters.
Abstract: This paper describes the process used in the
automation of the Maritime UAV commands using the Kinect sensor.
The AR Drone is a Quadrocopter manufactured by Parrot [1] to be
controlled using the Apple operating systems such as iPhones and
Ipads. However, this project uses the Microsoft Kinect SDK and
Microsoft Visual Studio C# (C sharp) software, which are compatible
with Windows Operating System for the automation of the navigation
and control of the AR drone.
The navigation and control software for the Quadrocopter runs on
a windows 7 computer. The project is divided into two sections; the
Quadrocopter control system and the Kinect sensor control system.
The Kinect sensor is connected to the computer using a USB cable
from which commands can be sent to and from the Kinect sensors.
The AR drone has Wi-Fi capabilities from which it can be connected
to the computer to enable transfer of commands to and from the
Quadrocopter.
The project was implemented in C#, a programming language that
is commonly used in the automation systems. The language was
chosen because there are more libraries already established in C# for
both the AR drone and the Kinect sensor.
The study will contribute toward research in automation of
systems using the Quadrocopter and the Kinect sensor for navigation
involving a human operator in the loop. The prototype created has
numerous applications among which include the inspection of vessels
such as ship, airplanes and areas that are not accessible by human
operators.
Abstract: This paper presents the Function Approximation
Technique (FAT) based adaptive impedance control for a robotic
finger. The force based impedance control is developed so that the
robotic finger tracks the desired force while following the reference
position trajectory, under unknown environment position and
uncertainties in finger parameters. The control strategy is divided into
two phases, which are the free and contact phases. Force error
feedback is utilized in updating the uncertain environment position
during contact phase. Computer simulations results are presented to
demonstrate the effectiveness of the proposed technique.
Abstract: This paper presents a fuzzy logic controlled shunt
active power filter used to compensate for harmonic distortion in three-phase four-wire systems. The shunt active filter employs a
simple method for the calculation of the reference compensation current based of Fast Fourier Transform. This presented filter is able
to operate in both balanced and unbalanced load conditions. A fuzzy
logic based current controller strategy is used to regulate the filter current and hence ensure harmonic free supply current. The validity
of the presented approach in harmonic mitigation is verified via
simulation results of the proposed test system under different loading
conditions.
Abstract: This paper present the implementation of a new ordering strategy on Successive Overrelaxation scheme on two dimensional boundary value problems. The strategy involve two directions alternatingly; from top and bottom of the solution domain. The method shows to significantly reduce the iteration number to converge. Four numerical experiments were carried out to examine the performance of the new strategy.
Abstract: This study aims to identify the current situation and
problems of environmental statement for major four home appliances
(refrigerators, washing machines, air conditioners and television
receivers) sold at online stores in Japan, and then to suggest how to
improve the situation, through a questionnaire survey conducted
among businesses that operate online stores and online malls with
multiple online stores. Results of the study boil down to:
(1) It is found out that environmental statement for the home
appliances at online stores have four problems; (i) less information
on “three Rs" and “chemical substances" than the one on “energy
conservation", (ii) cost for providing environmental statement, (iii)
issues associated with a label and mark placement, and (iv) issues
associated with energy conservation statement.
(2) Improvements are suggested for each of the four problems listed
above, and shown are (i) the effectiveness of, and need to promote, a
label and mark placement, (ii) cost burden on buyers, and (iii) need
of active efforts made by businesses and of dissemination of legal
regulations to businesses.
Abstract: The Combination of path planning and path following is the main purpose of this paper. This paper describes the developed practical approach to motion control of the MRL small size robots. An intelligent controller is applied to control omni-directional robots motion in simulation and real environment respectively. The Brain Emotional Learning Based Intelligent Controller (BELBIC), based on LQR control is adopted for the omni-directional robots. The contribution of BELBIC in improving the control system performance is shown as application of the emotional learning in a real world problem. Optimizing of the control effort can be achieved in this method too. Next the implicit communication method is used to determine the high level strategies and coordination of the robots. Some simple rules besides using the environment as a memory to improve the coordination between agents make the robots' decision making system. With this simple algorithm our team manifests a desirable cooperation.
Abstract: Many agricultural and especially greenhouse
applications like plant inspection, data gathering, spraying and
selective harvesting could be performed by robots. In this paper
multiple nonholonomic robots are used in order to create a desired
formation scheme for screening solar energy in a greenhouse through
data gathering. The formation consists from a leader and a team
member equipped with appropriate sensors. Each robot is dedicated
to its mission in the greenhouse that is predefined by the
requirements of the application. The feasibility of the proposed
application includes experimental results with three unmanned
ground vehicles (UGV).
Abstract: There are some existing Java benchmarks, application benchmarks as well as micro benchmarks or mixture both of them,such as: Java Grande, Spec98, CaffeMark, HBech, etc. But none of them deal with behaviors of multi tasks operating systems. As a result, the achieved outputs are not satisfied for performance evaluation engineers. Behaviors of multi tasks operating systems are based on a schedule management which is employed in these systems. Different processes can have different priority to share the same resources. The time is measured by estimating from applications started to it is finished does not reflect the real time value which the system need for running those programs. New approach to this problem should be done. Having said that, in this paper we present a new Java benchmark, named FHOJ benchmark, which directly deals with multi tasks behaviors of a system. Our study shows that in some cases, results from FHOJ benchmark are far more reliable in comparison with some existing Java benchmarks.
Abstract: This paper presents the averaging model of a buck
converter derived from the generalized state-space averaging method.
The sliding mode control is used to regulate the output voltage of the
converter and taken into account in the model. The proposed model
requires the fast computational time compared with those of the full
topology model. The intensive time-domain simulations via the exact
topology model are used as the comparable model. The results show
that a good agreement between the proposed model and the switching
model is achieved in both transient and steady-state responses. The
reported model is suitable for the optimal controller design by using
the artificial intelligence techniques.
Abstract: The aim of this study was to screen for
microorganism that able to utilize 3-N-trimethylamino-1-propanol
(homocholine) as a sole source of carbon and nitrogen. The aerobic
degradation of homocholine has been found by a gram-positive
Rhodococcus sp. bacterium isolated from soil. The isolate was
identified as Rhodococcus sp. strain A4 based on the phenotypic
features, physiologic and biochemical characteristics, and
phylogenetic analysis. The cells of the isolated strain grown on both
basal-TMAP and nutrient agar medium displayed elementary
branching mycelia fragmented into irregular rod and coccoid
elements. Comparative 16S rDNA sequencing studies indicated that
the strain A4 falls into the Rhodococcus erythropolis subclade and
forms a monophyletic group with the type-strains of R. opacus, and
R. wratislaviensis. Metabolites analysis by capillary electrophoresis,
fast atom bombardment-mass spectrometry, and gas
chromatography- mass spectrometry, showed trimethylamine (TMA)
as the major metabolite beside β-alanine betaine and
trimethylaminopropionaldehyde. Therefore, the possible degradation
pathway of trimethylamino propanol in the isolated strain is through
consequence oxidation of alcohol group (-OH) to aldehyde (-CHO)
and acid (-COOH), and thereafter the cleavage of β-alanine betaine
C-N bonds yielded trimethylamine and alkyl chain.
Abstract: Distant-talking voice-based HCI system suffers from
performance degradation due to mismatch between the acoustic
speech (runtime) and the acoustic model (training). Mismatch is
caused by the change in the power of the speech signal as observed at
the microphones. This change is greatly influenced by the change in
distance, affecting speech dynamics inside the room before reaching
the microphones. Moreover, as the speech signal is reflected, its
acoustical characteristic is also altered by the room properties. In
general, power mismatch due to distance is a complex problem. This
paper presents a novel approach in dealing with distance-induced
mismatch by intelligently sensing instantaneous voice power variation
and compensating model parameters. First, the distant-talking speech
signal is processed through microphone array processing, and the
corresponding distance information is extracted. Distance-sensitive
Gaussian Mixture Models (GMMs), pre-trained to capture both
speech power and room property are used to predict the optimal
distance of the speech source. Consequently, pre-computed statistic
priors corresponding to the optimal distance is selected to correct
the statistics of the generic model which was frozen during training.
Thus, model combinatorics are post-conditioned to match the power
of instantaneous speech acoustics at runtime. This results to an
improved likelihood in predicting the correct speech command at
farther distances. We experiment using real data recorded inside two
rooms. Experimental evaluation shows voice recognition performance
using our method is more robust to the change in distance compared
to the conventional approach. In our experiment, under the most
acoustically challenging environment (i.e., Room 2: 2.5 meters), our
method achieved 24.2% improvement in recognition performance
against the best-performing conventional method.
Abstract: Nowadays, with the emerging of the new applications
like robot control in image processing, artificial vision for visual
servoing is a rapidly growing discipline and Human-machine
interaction plays a significant role for controlling the robot. This
paper presents a new algorithm based on spatio-temporal volumes for
visual servoing aims to control robots. In this algorithm, after
applying necessary pre-processing on video frames, a spatio-temporal
volume is constructed for each gesture and feature vector is extracted.
These volumes are then analyzed for matching in two consecutive
stages. For hand gesture recognition and classification we tested
different classifiers including k-Nearest neighbor, learning vector
quantization and back propagation neural networks. We tested the
proposed algorithm with the collected data set and results showed the
correct gesture recognition rate of 99.58 percent. We also tested the
algorithm with noisy images and algorithm showed the correct
recognition rate of 97.92 percent in noisy images.