Abstract: The liquid cargo contained in a partly-filled road tank
vehicle is prone to dynamic slosh movement when subjected to
external disturbances. The slosh behavior has been identified as a
significant factor impairing the safety of liquid cargo transportation.
The laboratory experiments have been conducted for analyzing fluid
slosh in partly filled tanks. The experiment results measured under
forced harmonic excitations reveal the three-dimensional nature of
the fluid motion and coupling between the lateral and longitudinal
fluid slosh at resonance. Several spectral components are observed
for the transient slosh forces, which can be associated with the
excitation, resonance, and beat frequencies. The peak slosh forces
and moments in the vicinity of resonance are significantly larger than
those of the equivalent rigid mass. Due to the nature of coupling
between sloshing fluid and vehicle body, the issue of the dynamic
fluid-structure interaction is essential in the analysis of tank-vehicle
dynamics. A dynamic pitch plane model of a Tridem truck
incorporated the fluid slosh dynamics is developed to analyze the
fluid-vehicle interaction under the straight-line braking maneuvers.
The results show that the vehicle responses are highly associated
with the characteristics of fluid slosh force and moment.
Abstract: The presented paper shows the possibility of using
holographic interferometry for measurement of temperature field in
moving fluids. There are a few methods for identification of velocity
fields in fluids, such us LDA, PIV, hot wire anemometry. It is very
difficult to measure the temperature field in moving fluids. One of the
often used methods is Constant Current Anemometry (CCA), which
is a point temperature measurement method. Data are possibly
acquired at frequencies up to 1000Hz. This frequency should be
limiting factor for using of CCA in fluid when fast change of
temperature occurs. This shortcoming of CCA measurements should
be overcome by using of optical methods such as holographic
interferometry. It is necessary to employ a special holographic setup
with double sensitivity instead of the commonly used Mach-Zehnder
type of holographic interferometer in order to attain the parameters
sufficient for the studied case. This setup is not light efficient like the
Mach-Zehnder type but has double sensitivity. The special technique
of acquiring and phase averaging of results from holographic
interferometry is also presented. The results from the holographic
interferometry experiments will be compared with the temperature
field achieved by methods CCA method.
Abstract: Although there have been many researches in cluster
analysis to consider on feature weights, little effort is made on sample
weights. Recently, Yu et al. (2011) considered a probability
distribution over a data set to represent its sample weights and then
proposed sample-weighted clustering algorithms. In this paper, we
give a sample-weighted version of generalized fuzzy clustering
regularization (GFCR), called the sample-weighted GFCR
(SW-GFCR). Some experiments are considered. These experimental
results and comparisons demonstrate that the proposed SW-GFCR is
more effective than the most clustering algorithms.
Abstract: The White Kwao (Pueraria mirifica), a potent phytoestrogenic medicinal plant, has long been use in Thailand as a traditional folkmedicine. However, no scientific information of the direct effect of White Kwao on the development of mammalian embryo was available. Therefore, the purpose of this study was to investigate the effect of White Kwao extract on the in vitro development and implantation rate of mouse embryos. This study was designed into two experiments. In the first experiment, the two-cell stage mouse embryos were collected from the oviduct of superovulated mature female mice, and randomly cultured in three different media, the M16, M16 supplemented with 0.52μg esthinylestradiol-17β, and M16 supplemented with 10 mg/ml White Kwao extract. The culture was incubated in CO2 incubator at 37 oC . After the embryos were cultivated, the developments of embryos were observed every 24 hours for 5 days. The development rate of embryos from the two-cell stage to blastocyst stage in the media was with White Kwao was significantly higher (p
Abstract: The projection methods, usually viewed as the methods
for computing eigenvalues, can also be used to estimate pseudospectra.
This paper proposes a kind of projection methods for computing
the pseudospectra of large scale matrices, including orthogonalization
projection method and oblique projection method respectively. This
possibility may be of practical importance in applications involving
large scale highly nonnormal matrices. Numerical algorithms are
given and some numerical experiments illustrate the efficiency of
the new algorithms.
Abstract: commercially produced in Malaysia granular
palm shell activated carbon (PSAC) was biomodified with
bacterial biomass (Bacillus subtilis) to produce a hybrid
biosorbent of higher efficiency. The obtained biosorbent was
evaluated in terms of adsorption capacity to remove copper
and zinc metal ions from aqueous solutions. The adsorption
capacity was evaluated in batch adsorption experiments where
concentrations of metal ions varied from 20 to 350 mg/L. A
range of pH from 3 to 6 of aqueous solutions containing metal
ions was tested. Langmuir adsorption model was used to
interpret the experimental data. Comparison of the adsorption
data of the biomodified and original palm shell activated
carbon showed higher uptake of metal ions by the hybrid
biosorbent. A trend in metal ions uptake increase with the
increase in the solution-s pH was observed. The surface
characterization data indicated a decrease in the total surface
area for the hybrid biosorbent; however the uptake of copper
and zinc by it was at least equal to the original PSAC at pH 4
and 5. The highest capacity of the hybrid biosorbent was
observed at pH 5 and comprised 22 mg/g and 19 mg/g for
copper and zinc, respectively. The adsorption capacity at the
lowest pH of 3 was significantly low. The experimental results
facilitated identification of potential factors influencing the
adsorption of copper and zinc onto biomodified and original
palm shell activated carbon.
Abstract: In this paper we present an approach for 3D face
recognition based on extracting principal components of range
images by utilizing modified PCA methods namely 2DPCA and
bidirectional 2DPCA also known as (2D) 2 PCA.A preprocessing
stage was implemented on the images to smooth them using median
and Gaussian filtering. In the normalization stage we locate the nose
tip to lay it at the center of images then crop each image to a standard
size of 100*100. In the face recognition stage we extract the principal
component of each image using both 2DPCA and (2D) 2 PCA.
Finally, we use Euclidean distance to measure the minimum distance
between a given test image to the training images in the database. We
also compare the result of using both methods. The best result
achieved by experiments on a public face database shows that 83.3
percent is the rate of face recognition for a random facial expression.
Abstract: Smoke from domestic wood burning has been
identified as a major contributor to air pollution, motivating detailed
emission measurements under controlled conditions. A series of
experiments was performed to characterise the emissions from wood
combustion in a fireplace and in a woodstove of two common species
of trees grown in Spain: Pyrenean oak (Quercus pyrenaica) and
black poplar (Populus nigra). Volatile organic compounds (VOCs) in
the exhaust emissions were collected in Tedlar bags, re-sampled in
sorbent tubes and analysed by thermal desorption-gas
chromatography-flame ionisation detection. Pyrenean oak presented
substantially higher emissions in the woodstove than in the fireplace,
for the majority of compounds. The opposite was observed for
poplar. Among the 45 identified species, benzene and benzenerelated
compounds represent the most abundant group, followed by
oxygenated VOCs and aliphatics. Emission factors obtained in this
study are generally of the same order than those reported for
residential experiments in the USA.
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: Conventionally the selection of parameters depends
intensely on the operator-s experience or conservative technological
data provided by the EDM equipment manufacturers that assign
inconsistent machining performance. The parameter settings given by
the manufacturers are only relevant with common steel grades. A
single parameter change influences the process in a complex way.
Hence, the present research proposes artificial neural network (ANN)
models for the prediction of surface roughness on first commenced
Ti-15-3 alloy in electrical discharge machining (EDM) process. The
proposed models use peak current, pulse on time, pulse off time and
servo voltage as input parameters. Multilayer perceptron (MLP) with
three hidden layer feedforward networks are applied. An assessment
is carried out with the models of distinct hidden layer. Training of the
models is performed with data from an extensive series of
experiments utilizing copper electrode as positive polarity. The
predictions based on the above developed models have been verified
with another set of experiments and are found to be in good
agreement with the experimental results. Beside this they can be
exercised as precious tools for the process planning for EDM.
Abstract: In order to assess optical fiber reliability in different environmental and stress conditions series of testing are performed simulating overlapping of chemical and mechanical controlled varying factors. Each series of testing may be compared using statistical processing: i.e. Weibull plots. Due to the numerous data to treat, a software application has appeared useful to interpret selected series of experiments in function of envisaged factors. The current paper presents a software application used in the storage, modelling and interpretation of experimental data gathered from optical fibre testing. The present paper strictly deals with the software part of the project (regarding the modelling, storage and processing of user supplied data).
Abstract: Removal of a reactive dye (Reactive blue 4) by
adsorption utilizing waste aluminium hydroxide sludge as an
adsorbent was investigated. The removal of the dye was optimized
using response surface methodology (RSM). In the RSM
experiments; initial dye concentration, adsorbent concentration and
contact time were critical parameters. RSM experiments were
performed at the range of initial dye concentration 31.82-368.18
mg/L, adsorbent concentration 3.18-36.82 g/L, contact time 15.82-
56.18 h. Optimum initial dye concentration, adsorbent concentration
and contact time were obtained as 108.83 mg/L, 29.36 g/L and 33.57
h respectively. At these conditions, maximum removal of the dye was
obtained as 95%. The experiments were performed at the optimum
conditions to verify these results and the same results were obtained.
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: The main aim of this work is to establish the
capabilities of new green buildings to ascertain off-grid electricity
generation based on the integration of wind turbines in the
conceptual model of a rotating tower [2] in Dubai. An in depth
performance analysis of the WinWind 3.0MW [3] wind turbine is
performed. Data based on the Dubai Meteorological Services is
collected and analyzed in conjunction with the performance analysis
of this wind turbine. The mathematical model is compared with
Computational Fluid Dynamics (CFD) results based on a conceptual
rotating tower design model. The comparison results are further
validated and verified for accuracy by conducting experiments on a
scaled prototype of the tower design. The study concluded that
integrating wind turbines inside a rotating tower can generate enough
electricity to meet the required power consumption of the building,
which equates to a wind farm containing 9 horizontal axis wind
turbines located at an approximate area of 3,237,485 m2 [14].
Abstract: The aim of this study was to investigate the
effectiveness of anaerobic digestion for the treatment of wool
scouring wastes. The experiments design comprised three ratios of
waste (W) to seed(S) (W:S) of 25:75, 50:50 and 75:25, corresponding
to 1.9. 1.7 and 1.5g tCOD/g TS, respectively, with or without
chemicals addition. NH4Cl was added to the reactors as a source for
nitrogen to achieve C:N:P of 420:14:3. A cationic flocculent was
added at 0.5 and 0.75% to enhance flocculation of sludge. The results
showed that the reactors that received W:S at a ratio of 25:75
produced the largest volume of biogas. The final soluble COD
(sCOD) was below the limits for discharge to the sewer system.
Abstract: A fusion classifier composed of two modules, one made by a hidden Markov model (HMM) and the other by a support vector machine (SVM), is proposed to recognize faces with pose variations in open-set recognition settings. The HMM module captures the evolution of facial features across a subject-s face using the subject-s facial images only, without referencing to the faces of others. Because of the captured evolutionary process of facial features, the HMM module retains certain robustness against pose variations, yielding low false rejection rates (FRR) for recognizing faces across poses. This is, however, on the price of poor false acceptance rates (FAR) when recognizing other faces because it is built upon withinclass samples only. The SVM module in the proposed model is developed following a special design able to substantially diminish the FAR and further lower down the FRR. The proposed fusion classifier has been evaluated in performance using the CMU PIE database, and proven effective for open-set face recognition with pose variations. Experiments have also shown that it outperforms the face classifier made by HMM or SVM alone.
Abstract: We address the balancing problem of transfer lines in
this paper to find the optimal line balancing that minimizes the nonproductive
time. We focus on the tool change time and face
orientation change time both of which influence the makespane. We
consider machine capacity limitations and technological constraints
associated with the manufacturing process of auto cylinder heads.
The problem is represented by a mixed integer programming model
that aims at distributing the design features to workstations and
sequencing the machining processes at a minimum non-productive
time. The proposed model is solved by an algorithm established using
linearization schemes and Benders- decomposition approach. The
experiments show the efficiency of the algorithm in reaching the
exact solution of small and medium problem instances at reasonable
time.
Abstract: This paper proposes a new method for analyzing textual data. The method deals with items of textual data, where each item is described based on various viewpoints. The method acquires 2- class classification models of the viewpoints by applying an inductive learning method to items with multiple viewpoints. The method infers whether the viewpoints are assigned to the new items or not by using the models. The method extracts expressions from the new items classified into the viewpoints and extracts characteristic expressions corresponding to the viewpoints by comparing the frequency of expressions among the viewpoints. This paper also applies the method to questionnaire data given by guests at a hotel and verifies its effect through numerical experiments.
Abstract: The use of electronic sensors in the electronics
industry has become increasingly popular over the past few years,
and it has become a high competition product. The frequency
adjustment process is regarded as one of the most important process
in the electronic sensor manufacturing process. Due to inaccuracies
in the frequency adjustment process, up to 80% waste can be caused
due to rework processes; therefore, this study aims to provide a
preliminary understanding of the role of parameters used in the
frequency adjustment process, and also make suggestions in order to
further improve performance. Four parameters are considered in this
study: air pressure, dispensing time, vacuum force, and the distance
between the needle tip and the product. A full factorial design for
experiment 2k was considered to determine those parameters that
significantly affect the accuracy of the frequency adjustment process,
where a deviation in the frequency after adjustment and the target
frequency is expected to be 0 kHz. The experiment was conducted on
two levels, using two replications and with five center-points added.
In total, 37 experiments were carried out. The results reveal that air
pressure and dispensing time significantly affect the frequency
adjustment process. The mathematical relationship between these
two parameters was formulated, and the optimal parameters for air
pressure and dispensing time were found to be 0.45 MPa and 458 ms,
respectively. The optimal parameters were examined by carrying out
a confirmation experiment in which an average deviation of 0.082
kHz was achieved.
Abstract: The present work was conducted to find out the effect
of biofertilizer formulated with four species of bacteria (two species
of Azotobacter and two species of Lysobacter) and zinc sulphate.
Field experiments with mustard plant were conducted to study the
effectiveness of soil application of zinc sulphate and biofertilizer at
0, 10, 20, 30, 40, 50 days after sowing. Plant height and condition of
plant was found to be increased significantly using a mixture of
biofertilizer and zinc sulphate than other treatments after 40 days
sowing. Three treatments were also used in this field experiment such
as bacteria only, zinc sulphate only and mixture of biofertilizer and
zinc sulphate. The treatment using a mixture of zinc sulphate and
biofertilizer had the best yield (4688.008 kg/ha) within 50 days of
sowing and performed better than other treatments. Field experiment
using zinc sulphate only was second best yield (3380.75Kg/ha) and
biofertilizer only treatment gave (2639.04kg/ha).