Abstract: Rotation or tilt present in an image capture by digital
means can be detected and corrected using Artificial Neural Network
(ANN) for application with a Face Recognition System (FRS). Principal
Component Analysis (PCA) features of faces at different angles
are used to train an ANN which detects the rotation for an input image
and corrected using a set of operations implemented using another
system based on ANN. The work also deals with the recognition
of human faces with features from the foreheads, eyes, nose and
mouths as decision support entities of the system configured using
a Generalized Feed Forward Artificial Neural Network (GFFANN).
These features are combined to provide a reinforced decision for
verification of a person-s identity despite illumination variations. The
complete system performing facial image rotation detection, correction
and recognition using re-enforced decision support provides a
success rate in the higher 90s.
Abstract: Mostly the systems are dealing with time varying
signals. The Power efficiency can be achieved by adapting the system
activity according to the input signal variations. In this context
an adaptive rate filtering technique, based on the level crossing sampling
is devised. It adapts the sampling frequency and the filter order
by following the input signal local variations. Thus, it correlates the
processing activity with the signal variations. Interpolation is required
in the proposed technique. A drastic reduction in the interpolation
error is achieved by employing the symmetry during the interpolation
process. Processing error of the proposed technique is
calculated. The computational complexity of the proposed filtering
technique is deduced and compared to the classical one. Results
promise a significant gain of the computational efficiency and hence
of the power consumption.
Abstract: Polystyrene particles of different sizes are optically
trapped with a gaussian beam from a He-Cd laser operating at 442
nm. The particles are observed to exhibit luminescence after a certain
trapping time followed by an escape from the optical trap. The
observed luminescence is explained in terms of the photodegradation
of the polystyrene backbone. It is speculated that these chemical
modifications also play a role for the escape of the particles from the
trap. Variations of the particle size and the laser power show that
these parameters have a great influence on the observed phenomena.
Abstract: This paper examines the use of mechanical aerator for
oxidation-ditch process. The rotor, which controls the aeration, is the
main component of the aeration process. Therefore, the objective of
this study is to find out the variations in overall oxygen transfer
coefficient (KLa) and aeration efficiency (AE) for different
configurations of aerator by varying the parameters viz. speed of
aerator, depth of immersion, blade tip angles so as to yield higher
values of KLa and AE. Six different configurations of aerator were
developed and fabricated in the laboratory and were tested for abovementioned
parameters. The curved blade rotor (CBR) emerged as a
potential aerator with blade tip angle of 47°.
The mathematical models are developed for predicting the
behaviour of CBR w.r.t kLa and power. In laboratory studies, the
optimum value of KLa and AE were observed to be 10.33 h-1 and
2.269 kg O2/ kWh.
Abstract: The Object of this paper is to design and analyze a
Hysteresis modulation based sliding mode control (HMSMC) for
positive output elementary super lift Luo converter (POESLLC),
which is the start-of-the-art DC-DC converter. The positive output
elementary super lift Luo converter performs the voltage
conversion from positive source voltage to positive load voltage.
This paper proposes a HMSMC capable of providing the good
steady state and dynamic performance compared to conventional
controllers. Dynamic equations describing the positive output
elementary super lift luo converter are derived by using state space
average method. The simulation model of the positive output
elementary super lift Luo converter with its control circuit is
implemented in Matlab/Simulink. The HMSMC for positive
output elementary super lift Luo converter is tested for line
changes, load changes and also for components variations.
Abstract: In this paper, the ice melting in rectangular,
cylindrical and conical forms, which are erected vertically against air
flow, are experimentally studied in the free convection regime.The
results obtained are: Nusslet Number, heat transfer coefficient
andGrashof Number, and the variations of the said numbers in
relation to the time. The variations of ice slab area and volume are
measured, too.
Abstract: Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.
Abstract: Pressure waves and Water Hammer occur in a
pumping system when valves are closed or opened suddenly or in
the case of sudden failure of pumps. Determination of maximum
water hammer is considered one of the most important technical
and economical items of which engineers and designers of
pumping stations and conveyance pipelines should take care.
Hammer Software is a recent application used to simulate water
hammer. The present study focuses on determining significance of
each input parameter of the application relative to the maximum
amount of water hammer estimated by the software. The study
determines estimated maximum water hammer variations due to
variations of input parameters including water temperature, pipe
type, thickness and diameter, electromotor rpm and power, and
moment of inertia of electromotor and pump. In our study,
Kuhrang Pumping Station was modeled using WaterGEMS
Software. The pumping station is characterized by total discharge
of 200 liters per second, dynamic height of 194 meters and 1.5
kilometers of steel conveyance pipeline and transports water to
Cheshme Morvarid for farmland irrigation. The model was run in
steady hydraulic condition and transferred to Hammer Software.
Then, the model was run in several unsteady hydraulic conditions
and sensitivity of maximum water hammer to each input parameter
was calculated. It is shown that parameters to which maximum
water hammer is most sensitive are moment of inertia of pump and
electromotor, diameter, type and thickness of pipe and water
temperature, respectively.
Abstract: This study investigated the relationship between urban
and rural ozone concentrations and quantified the extent to which
ambient rural conditions and the concentrations of other pollutants
can be used to predict urban ozone concentrations. The study
describes the variations of ozone in weekday and weekends as well as
the daily maximum recorded at selected monitoring stations. The
results showed that Putrajaya station had the highest concentrations
of O3 on weekend due the titration of NO during the weekday.
Additionally, Jerantut had the lowest average concentration with a
reading value high on Wednesdays. The comparisons of average and
maximum concentrations of ozone for the three stations showed that
the strongest significant correlation is recorded in Jerantut station
with the value R2= 0.769. Ozone concentrations originating from a
neighbouring urban site form a better predictor to the urban ozone
concentrations than widespread rural ozone at some levels of
temporal averaging. It is found that in urban and rural of Malaysian
peninsular, the concentration of ozone depends on the concentration
of NOx and seasonal meteorological factors. The HYSPLIT Model
(the northeast monsoon) showed that the wind direction can also
influence the concentration of ozone in the atmosphere in the studied
areas.
Abstract: Detection of player identity is challenging task in sport video content analysis. In case of soccer video player number recognition is effective and precise solution. Jersey numbers can be considered as scene text and difficulties in localization and recognition appear due to variations in orientation, size, illumination, motion etc. This paper proposed new method for player number localization and recognition. By observing hue, saturation and value for 50 different jersey examples we noticed that most often combination of low and high saturated pixels is used to separate number and jersey region. Image segmentation method based on this observation is introduced. Then, novel method for player number localization based on internal contours is proposed. False number candidates are filtered using area and aspect ratio. Before OCR processing extracted numbers are enhanced using image smoothing and rotation normalization.
Abstract: One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.
Abstract: In many applications, magnetic suspension systems
are required to operate over large variations in air gap. As a result,
the nonlinearities inherent in most types of suspensions have a
significant impact on performance. Specifically, it may be difficult to
design a linear controller which gives satisfactory performance,
stability, and disturbance rejection over a wide range of operating
points. in this paper an optimal controller based on discontinuous
mathematical model of the system for an electromagnetic suspension
system which is applied in magnetic trains has been designed .
Simulations show that the new controller can adapt well to the
variance of suspension mass and gap, and keep its dynamic
performance, thus it is superior to the classic controller.
Abstract: Cardiac pulse-related artifacts in the EEG recorded
simultaneously with fMRI are complex and highly variable. Their
effective removal is an unsolved problem. Our aim is to develop an
adaptive removal algorithm based on the matching pursuit (MP)
technique and to compare it to established methods using a visual
evoked potential (VEP). We recorded the VEP inside the static
magnetic field of an MR scanner (with artifacts) as well as in an
electrically shielded room (artifact free). The MP-based artifact
removal outperformed average artifact subtraction (AAS) and
optimal basis set removal (OBS) in terms of restoring the EEG field
map topography of the VEP. Subsequently, a dipole model was fitted
to the VEP under each condition using a realistic boundary element
head model. The source location of the VEP recorded inside the MR
scanner was closest to that of the artifact free VEP after cleaning
with the MP-based algorithm as well as with AAS. While none of the
tested algorithms offered complete removal, MP showed promising
results due to its ability to adapt to variations of latency, frequency
and amplitude of individual artifact occurrences while still utilizing a
common template.
Abstract: In this research a mathematical model for direct
oxidization of hydrogen sulfide into elemental sulfur in a fluidized
bed reactor with external circulation was developed. As the catalyst
is deactivated in the fluidized bed, it might be placed in a reduction
tank in order to remove sulfur through heating above its dew point.
The reactor model demonstrated via MATLAB software. It was
shown that variations of H2S conversion as well as; products formed
were reasonable in comparison with corresponding results of a fixed
bed reactor. Through analyzing results of this model, it became
possible to propose the main optimized operating conditions for the
process considered. These conditions included; the temperature range
of 100-130ºC and utilizing the catalyst as much as possible providing
the highest bed density respect to dimensions of bed, economical
aspects that the bed ever remained in fluidized mode. A high active
and stable catalyst under the optimum conditions exhibited 100%
conversion in a fluidized bed reactor.
Abstract: This paper proposed high level feature for online Lao handwritten recognition. This feature must be high level enough so that the feature is not change when characters are written by different persons at different speed and different proportion (shorter or longer stroke, head, tail, loop, curve). In this high level feature, a character is divided in to sequence of curve segments where a segment start where curve reverse rotation (counter clockwise and clockwise). In each segment, following features are gathered cumulative change in direction of curve (- for clockwise), cumulative curve length, cumulative length of left to right, right to left, top to bottom and bottom to top ( cumulative change in X and Y axis of segment). This feature is simple yet robust for high accuracy recognition. The feature can be gather from parsing the original time sampling sequence X, Y point of the pen location without re-sampling. We also experiment on other segmentation point such as the maximum curvature point which was widely used by other researcher. Experiments results show that the recognition rates are at 94.62% in comparing to using maximum curvature point 75.07%. This is due to a lot of variations of turning points in handwritten.
Abstract: This paper reports a new pattern recognition approach for face recognition. The biological model of light receptors - cones and rods in human eyes and the way they are associated with pattern vision in human vision forms the basis of this approach. The functional model is simulated using CWD and WPD. The paper also discusses the experiments performed for face recognition using the features extracted from images in the AT & T face database. Artificial Neural Network and k- Nearest Neighbour classifier algorithms are employed for the recognition purpose. A feature vector is formed for each of the face images in the database and recognition accuracies are computed and compared using the classifiers. Simulation results show that the proposed method outperforms traditional way of feature extraction methods prevailing for pattern recognition in terms of recognition accuracy for face images with pose and illumination variations.
Abstract: In this paper, an intelligent automatic parking control method is proposed. First, the dynamical equation of the rear parking control is derived. Then a fuzzy logic control is proposed to perform the parking planning process. Further, a rear neural network is proposed for the steering control. Through the simulations and experiments, the intelligent auto-parking mode controllers have been shown to achieve the demanded goals with satisfactory control performance and to guarantee the system robustness under parametric variations and external disturbances. To improve some shortcomings and limitations in conventional parking mode control and further to reduce consumption time and prime cost.
Abstract: A parametric study of a mixed-compression
supersonic inlet is performed and reported. The effects of inlet Mach
Numbers, varying from 4 to 10, and angle of attack, varying from 0
to 10, are reported for a constant inlet dynamic pressure. The paper
looked at the variations of mass flow rates through the inlet, gain in
entropy through the inlet, and the angles of the external oblique
shocks. The mass flow rates were found to decrease monotonically
with Mach numbers and increase with angle of attacks. On the other
hand the entropy gain through the inlet increased with increasing
Mach number and angle of attack. The variation in static pressure
was found to be identical from the inlet throat to the exit for Mach
number values higher than 6.
Abstract: The aim of our research was to evaluate the effects of
physical exercise on lipid profile and anthropometric characteristics
in young subjects, diagnosed with metabolic syndrome (MS). The
study has been developed during 28 weeks on 20 young obese
patients which have undertaken an intermittent submaximal exercise
program. After 28 weeks of physical activity, the results show
significant effects on anthropometric characteristics and serum lipid
profile of research subjects. Additionally, the results of this study
confirms the major correlation between the variations of
intraabdominal adiposity, determined ultrasonographycally,
and the changes of serum lipid concentrations, a better
correlation than it is used abdominal circumference or body
weight index.
Abstract: The distribution of macrobenthic polychaetes along
the coastal waters of Penang National Park was surveyed to estimate
the effect of various environmental parameters at three stations
(200m, 600m and 1200m) from the shoreline, during six sampling
months, from June 2010 to April 2011.The use of polychaetes in
descriptive ecology is surveyed in the light of a recent investigation
particularly concerning the soft bottom biota environments.
Polychaetes, often connected in the former to the notion of
opportunistic species able to proliferate after an enhancement in
organic matter, had performed a momentous role particularly with
regard to effected soft-bottom habitats. The objective of this survey
was to investigate different environment stress over soft bottom
polychaete community along Teluk Ketapang and Pantai Acheh
(Penang National Park) over a year period. Variations in the
polychaete community were evaluated using univariate and
multivariate methods. The results of PCA analysis displayed a
positive relation between macrobenthic community structures and
environmental parameters such as sediment particle size and organic
matter in the coastal water. A total of 604 individuals were examined
which was grouped into 23 families. Family Nereidae was the most
abundant (22.68%), followed by Spionidae (22.02%), Hesionidae
(12.58%), Nephtylidae (9.27%) and Orbiniidae (8.61%). It is
noticeable that good results can only be obtained on the basis of good
taxonomic resolution. We proposed that, in monitoring surveys,
operative time could be optimized not only by working at a highertaxonomic
level on the entire macrobenthic data set, but by also
choosing an especially indicative group and working at lower
taxonomic and good level.