Abstract: One of the robust fault detection filter (RFDF)
designing method is based on sliding-mode theory. The main purpose
of our study is to introduce an innovative simplified reference
residual model generator to formulate the RFDF as a sliding-mode
observer without any manipulation package or transformation matrix,
through which the generated residual signals can be evaluated. So the
proposed design is more explicit and requires less design parameters
in comparison with approaches requiring changing coordinates. To
the best author's knowledge, this is the first time that the sliding
mode technique is applied to detect actuator and sensor faults in a
real boiler. The designing procedure is proposed in a drum boiler in
Synvendska Kraft AB Plant in Malmo, Sweden as a multivariable
and strongly coupled system. It is demonstrated that both sensor and
actuator faults can robustly be detected. Also sensor faults can be
diagnosed and isolated through this method.
Abstract: Mobile ad-hoc networks (MANETs) are a form of
wireless networks which do not require a base station for providing
network connectivity. Mobile ad-hoc networks have many
characteristics which distinguish them from other wireless networks
which make routing in such networks a challenging task. Cluster
based routing is one of the routing schemes for MANETs in which
various clusters of mobile nodes are formed with each cluster having
its own clusterhead which is responsible for routing among clusters.
In this paper we have proposed and implemented a distributed
weighted clustering algorithm for MANETs. This approach is based
on combined weight metric that takes into account several system
parameters like the node degree, transmission range, energy and
mobility of the nodes. We have evaluated the performance of
proposed scheme through simulation in various network situations.
Simulation results show that proposed scheme outperforms the
original distributed weighted clustering algorithm (DWCA).
Abstract: Cry j 1 is a causative substance of Japanese cedar
pollinosis, and it may deteriorate by Cry j 1 invasion to a lower
respiratory tract. We observed airborne particles containing Cry j 1 by
an immunofluorescence technique using a fluorescence microscope,
and we clarified that Cry j 1 exist as aggregates of airborne fine
particles (< 1.1 μm) in the urban atmosphere. Airborne Cry j 1 may
react with air pollutants and be denature to a substance deteriorated
Japanese cedar pollinosis. Therefore, we applied a sodium dodecyl
sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to evaluate a
Cry j 1 reacted with various air pollutants by liquid phase reaction,
and calculated kinetics constants of Cry j 1 extracted from pollens
collected in various sites and airborne fine particles containing Cry j
1 by using a surface plasmon resonance (SPR) method. As a result, it
is suggested that Cry j 1 may be denatured by air pollutants during
the transportation to the urban atmosphere.
Abstract: In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.
Abstract: Today, money laundering (ML) poses a serious threat
not only to financial institutions but also to the nation. This criminal
activity is becoming more and more sophisticated and seems to have
moved from the cliché of drug trafficking to financing terrorism and
surely not forgetting personal gain. Most international financial
institutions have been implementing anti-money laundering solutions
(AML) to fight investment fraud. However, traditional investigative
techniques consume numerous man-hours. Recently, data mining
approaches have been developed and are considered as well-suited
techniques for detecting ML activities. Within the scope of a
collaboration project for the purpose of developing a new solution for
the AML Units in an international investment bank, we proposed a
data mining-based solution for AML. In this paper, we present a
heuristics approach to improve the performance for this solution. We
also show some preliminary results associated with this method on
analysing transaction datasets.
Abstract: This paper presents a new technique for detection of
human faces within color images. The approach relies on image
segmentation based on skin color, features extracted from the two-dimensional
discrete cosine transform (DCT), and self-organizing
maps (SOM). After candidate skin regions are extracted, feature
vectors are constructed using DCT coefficients computed from those
regions. A supervised SOM training session is used to cluster feature
vectors into groups, and to assign “face" or “non-face" labels to those
clusters. Evaluation was performed using a new image database of
286 images, containing 1027 faces. After training, our detection
technique achieved a detection rate of 77.94% during subsequent
tests, with a false positive rate of 5.14%. To our knowledge, the
proposed technique is the first to combine DCT-based feature
extraction with a SOM for detecting human faces within color
images. It is also one of a few attempts to combine a feature-invariant
approach, such as color-based skin segmentation, together with
appearance-based face detection. The main advantage of the new
technique is its low computational requirements, in terms of both
processing speed and memory utilization.
Abstract: To understand working features of a micro combustor,
a computer code has been developed to study combustion of
hydrogen–air mixture in a series of chambers with same shape aspect
ratio but various dimensions from millimeter to micrometer level.
The prepared algorithm and the computer code are capable of
modeling mixture effects in different fluid flows including chemical
reactions, viscous and mass diffusion effects. The effect of various
heat transfer conditions at chamber wall, e.g. adiabatic wall, with
heat loss and heat conduction within the wall, on the combustion is
analyzed. These thermal conditions have strong effects on the
combustion especially when the chamber dimension goes smaller and
the ratio of surface area to volume becomes larger.
Both factors, such as larger heat loss through the chamber wall
and smaller chamber dimension size, may lead to the thermal
quenching of micro-scale combustion. Through such systematic
numerical analysis, a proper operation space for the micro-combustor
is suggested, which may be used as the guideline for microcombustor
design. In addition, the results reported in this paper
illustrate that the numerical simulation can be one of the most
powerful and beneficial tools for the micro-combustor design,
optimization and performance analysis.
Abstract: This paper presents a new adaptive DMC controller
that improves the controller performance in case of plant-model
mismatch. The new controller monitors the plant measured output,
compares it with the model output and calculates weights applied to
the controller move. Simulations show that the new controller can
help improve control performance and avoid instability in case of
severe model mismatches.
Abstract: We demonstrate the synthesis of intermediary views
within a sequence of color encoded, materials discriminating, X-ray
images that exhibit animated depth in a visual display. During the
image acquisition process, the requirement for a linear X-ray detector
array is replaced by synthetic image. Scale Invariant Feature
Transform, SIFT, in combination with material segmented morphing
is employed to produce synthetic imagery. A quantitative analysis of
the feature matching performance of the SIFT is presented along with
a comparative study of the synthetic imagery. We show that the total
number of matches produced by SIFT reduces as the angular
separation between the generating views increases. This effect is
accompanied by an increase in the total number of synthetic pixel
errors. The trends observed are obtained from 15 different luggage
items. This programme of research is in collaboration with the UK
Home Office and the US Dept. of Homeland Security.
Abstract: In the present study, the incorporation of graphene
into blends of acrylonitrile-butadiene-styrene terpolymer with
polypropylene (ABS/PP) was investigated focusing on the
improvement of their thermomechanical characteristics and the effect
on their rheological behavior. The blends were prepared by melt
mixing in a twin-screw extruder and were characterized by measuring
the MFI as well as by performing DSC, TGA and mechanical tests.
The addition of graphene to ABS/PP blends tends to increase their
melt viscosity, due to the confinement of polymer chains motion.
Also, graphene causes an increment of the crystallization temperature
(Tc), especially in blends with higher PP content, because of the
reduction of surface energy of PP nucleation, which is a consequence
of the attachment of PP chains to the surface of graphene through the
intermolecular CH-π interaction. Moreover, the above nanofiller
improves the thermal stability of PP and increases the residue of
thermal degradation at all the investigated compositions of blends,
due to the thermal isolation effect and the mass transport barrier
effect. Regarding the mechanical properties, the addition of graphene
improves the elastic modulus, because of its intrinsic mechanical
characteristics and its rigidity, and this effect is particularly strong in
the case of pure PP.
Abstract: This paper deals with the application of artificial
neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy
Inference System(ANFIS) approach to Load Frequency Control
(LFC) of multi unequal area hydro-thermal interconnected power
system. The proposed ANFIS controller combines the advantages of
fuzzy controller as well as quick response and adaptability nature of
ANN. Area-1 and area-2 consists of thermal reheat power plant
whereas area-3 and area-4 consists of hydro power plant with electric
governor. Performance evaluation is carried out by using intelligent
controller like ANFIS, ANN and Fuzzy controllers and conventional
PI and PID control approaches. To enhance the performance of
intelligent and conventional controller sliding surface is included.
The performances of the controllers are simulated using
MATLAB/SIMULINK package. A comparison of ANFIS, ANN,
Fuzzy, PI and PID based approaches shows the superiority of
proposed ANFIS over ANN & fuzzy, PI and PID controller for 1%
step load variation.
Abstract: Atherosclerosis was identified as a chronic inflammatory process resulting from interactions between plasma lipoproteins, cellular components (monocyte, macrophages, T lymphocytes, endothelial cells and smooth muscle cells) and the extracellular matrix of the arterial wall. Several types of genes were known to express during formation of atherosclerosis. This study is carried out to identify unknown differentially expressed gene (DEG) in atherogenesis. Rabbit’s aorta tissues were stained by H&E for histomorphology. GeneFishing™ PCR analysis was performed from total RNA extracted from the aorta tissues. The DNA fragment from DEG was cloned, sequenced and validated by Real-time PCR. Histomorphology showed intimal thickening in the aorta. DEG detected from ACP-41 was identified as cathepsin B gene and showed upregulation at week-8 and week-12 of atherogenesis. Therefore, ACP-based GeneFishing™ PCR facilitated identification of cathepsin B gene which was differentially expressed during development of atherosclerosis.
Abstract: This paper aims to study decomposition behavior in
pyrolytic environment of four lignocellulosic biomass (oil palm shell,
oil palm frond, rice husk and paddy straw), and two commercial
components of biomass (pure cellulose and lignin), performed in a
thermogravimetry analyzer (TGA). The unit which consists of a
microbalance and a furnace flowed with 100 cc (STP) min-1 Nitrogen,
N2 as inert. Heating rate was set at 20⁰C min-1 and temperature
started from 50 to 900⁰C. Hydrogen gas production during the
pyrolysis was observed using Agilent Gas Chromatography Analyzer
7890A. Oil palm shell, oil palm frond, paddy straw and rice husk
were found to be reactive enough in a pyrolytic environment of up to
900°C since pyrolysis of these biomass starts at temperature as low as
200°C and maximum value of weight loss is achieved at about
500°C. Since there was not much different in the cellulose,
hemicelluloses and lignin fractions between oil palm shell, oil palm
frond, paddy straw and rice husk, the T-50 and R-50 values obtained
are almost similar. H2 productions started rapidly at this temperature
as well due to the decompositions of biomass inside the TGA.
Biomass with more lignin content such as oil palm shell was found to
have longer duration of H2 production compared to materials of high
cellulose and hemicelluloses contents.
Abstract: In the upstream we place a piece of ring and rotate
it with 83Hz, 166Hz, 333Hz,and 666H to find the effect of the
periodic distortion.In the experiment this type of the perturbation
will not allow since the mechanical failure of any parts of the
equipment in the upstream will destroy the blade system. This type of
study will be only possible by CFD. We use two pumps NS32
(ENSAM) and three blades pump (Tamagawa Univ). The benchmark
computations were performed without perturbation parts, and confirm
the computational results well agreement in head-flow rate. We
obtained the pressure fluctuation growth rate that is representing the
global instability of the turbo-system. The fluctuating torque
components were 0.01Nm(5000rpm), 0.1Nm(10000rmp),
0.04Nm(20000rmp), 0.15Nm( 40000rmp) respectively. Only for
10000rpm(166Hz) the output toque was random, and it implies that it
creates unsteady flow by separations on the blades, and will reduce the
pressure loss significantly
Abstract: Leave of absence is important in maintaining a good
status of human resource quality. Allowing the employees temporarily
free from the routine assignments can vitalize the workers- morality
and productivity. This is particularly critical to secure a satisfactory
service quality for healthcare professionals of which were typically
featured with labor intensive and complicated works to perform. As
one of the veteran hospitals that were found and operated by the
Veteran Department of Taiwan, the nursing staff of the case hospital
was squeezed to an extreme minimum level under the pressure of a
tight budgeting. Leave of absence on schedule became extremely
difficult, especially for the intensive care units (ICU), in which
required close monitoring over the cared patients, and that had more
easily driven the ICU nurses nervous. Even worse, the deferred leaves
were more than 10 days at any time in the ICU because of a fluctuating
occupancy. As a result, these had brought a bad setback to this
particular nursing team, and consequently defeated the job
performance and service quality. To solve this problem and
accordingly to strengthen their morality, a project team was organized
across different departments specific for this. Sufficient information
regarding jobs and positions requirements, labor resources, and actual
working hours in detail were collected and analyzed in the team
meetings. Several alternatives were finalized. These included job
rotating, job combination, leave on impromptu and cross-departmental
redeployment. Consequently, the deferred leave days sharply reduced
70% to a level of 3 or less days. This improvement had not only
provided good shelter for the ICU nurses that improved their job
performance and patient safety but also encouraged the nurses active
participating of a project and learned the skills of solving problems
with colleagues.
Abstract: In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence.
Abstract: A robot simulator was developed to measure and
investigate the performance of a robot navigation system based on
the relative position of the robot with respect to random obstacles in
any two dimensional environment. The presented simulator focuses
on investigating the ability of a fuzzy-neural system for object
avoidance. A navigation algorithm is proposed and used to allow
random navigation of a robot among obstacles when the robot faces
an obstacle in the environment. The main features of this simulator
can be used for evaluating the performance of any system that can
provide the position of the robot with respect to obstacles in the
environment. This allows a robot developer to investigate and
analyze the performance of a robot without implementing the
physical robot.
Abstract: Reinforced concrete crash barriers used in road traffic
must meet a number of criteria. Crash barriers are laid lengthwise,
one behind another, and joined using specially designed steel locks.
While developing BSV reinforced concrete crash barriers (type
ŽPSV), experiments and calculations aimed to optimize the shape of
a newly designed lock and the reinforcement quantity and
distribution in a crash barrier were carried out. The tension carrying
capacity of two parallelly joined locks was solved experimentally.
Based on the performed experiments, adjustments of nonlinear
properties of steel were performed in the calculations. The obtained
results served as a basis to optimize the lock design using a
computational model that takes into account the plastic behaviour of
steel and the influence of the surrounding concrete [6]. The response
to the vehicle impact has been analyzed using a specially elaborated
complex computational model, comprising both the nonlinear model
of the damping wall or crash barrier and the detailed model of the
vehicle [7].
Abstract: A different concept for designing and detailing of
reinforced concrete precast frame structures is analyzed in this paper.
The new detailing of the joints derives from the special hybrid
moment frame joints. The special reinforcements of this alternative
detailing, named modified special hybrid joint, are bondless with
respect to both column and beams. Full scale tests were performed on
a plan model, which represents a part of 5 story structure, cropped in
the middle of the beams and columns spans. Theoretical approach
was developed, based on testing results on twice repaired model,
subjected to lateral seismic type loading. Discussion regarding the
modified special hybrid joint behavior and further on widening
research needed concludes the presentation.
Abstract: Color image segmentation can be considered as a
cluster procedure in feature space. k-means and its adaptive
version, i.e. competitive learning approach are powerful tools
for data clustering. But k-means and competitive learning suffer
from several drawbacks such as dead-unit problem and need to
pre-specify number of cluster. In this paper, we will explore to
use competitive and cooperative learning approach to perform
color image segmentation. In competitive and cooperative
learning approach, seed points not only compete each other, but
also the winner will dynamically select several nearest
competitors to form a cooperative team to adapt to the input
together, finally it can automatically select the correct number
of cluster and avoid the dead-units problem. Experimental
results show that CCL can obtain better segmentation result.