Abstract: Evolution strategy (ES) is a well-known instance of evolutionary algorithms, and there have been many studies on ES. In this paper, the author proposes an extended ES for solving fuzzy-valued optimization problems. In the proposed ES, genotype values are not real numbers but fuzzy numbers. Evolutionary processes in the ES are extended so that it can handle genotype instances with fuzzy numbers. In this study, the proposed method is experimentally applied to the evolution of neural networks with fuzzy weights and biases. Results reveal that fuzzy neural networks evolved using the proposed ES with fuzzy genotype values can model hidden target fuzzy functions even though no training data are explicitly provided. Next, the proposed method is evaluated in terms of variations in specifying fuzzy numbers as genotype values. One of the mostly adopted fuzzy numbers is a symmetric triangular one that can be specified by its lower and upper bounds (LU) or its center and width (CW). Experimental results revealed that the LU model contributed better to the fuzzy ES than the CW model, which indicates that the LU model should be adopted in future applications of the proposed method.
Abstract: Due to the interference effects, the intrinsic
aerodynamic parameters obtained from the individual component
testing are always fundamentally different than those obtained for
complete model testing. Consideration and limitation for such testing
need to be taken into account in any design work related to the
component buildup method. In this paper, the scaled model of a
straight rectangular canard of a hybrid buoyant aircraft is tested at 50
m/s in IIUM-LSWT (Low Speed Wind Tunnel). Model and its
attachment with the balance are kept rigid to have results free from
the aeroelastic distortion. Based on the velocity profile of the test
section’s floor; the height of the model is kept equal to the
corresponding boundary layer displacement. Balance measurements
provide valuable but limited information of overall aerodynamic
behavior of the model. Zero lift coefficient is obtained at -2.2o and
the corresponding drag coefficient was found to be less than that at
zero angle of attack. As a part of the validation of low fidelity tool,
plot of lift coefficient plot was verified by the experimental data and
except the value of zero lift coefficients, the overall trend has under
predicted the lift coefficient. Based on this comparative study, a
correction factor of 1.36 is proposed for lift curve slope obtained
from the panel method.
Abstract: In this study, failure analysis of pipe system at a micro
hydroelectric power plant is investigated. Failure occurred at the pipe
system in the powerhouse during shut down operation of the water
flow by a valve. This locking had caused a sudden shock wave, also
called “Water-hammer effect”, resulting in noise and inside pressure
increase. After visual investigation of the effect of the shock wave on
the system, a circumference crack was observed at the pipe flange
weld region. To establish the reason for crack formation, calculations
of pressure and stress values at pipe, flange and welding seams were
carried out and concluded that safety factor was high (2.2), indicating
that no faulty design existed. By further analysis, pipe system and
hydroelectric power plant was examined. After observations it is
determined that the plant did not include a ventilation nozzle (air
trap), that prevents the system of sudden pressure increase inside the
pipes which is caused by water-hammer effect. Analyses were carried
out to identify the influence of water-hammer effect on inside
pressure increase and it was concluded that, according Jowkowsky’s
equation, shut down time is effective on inside pressure increase. The
valve closing time was uncertain but by a shut down time of even one
minute, inside pressure would increase by 7.6 bar (working pressure
was 34.6 bar). Detailed investigations were also carried out on the
assembly of the pipe-flange system by considering technical
drawings. It was concluded that the pipe-flange system was not
installed according to the instructions. Two of five weld seams were
not applied and one weld was carried out faulty. This incorrect and
inadequate weld seams resulted in; insufficient connection of the pipe
to the flange constituting a strong notch effect at weld seam regions,
increase in stress values and the decrease of strength and safety
factor.
Abstract: The nickel-manganese (Ni-Mn) alloy coating prepared
from DC electrodeposition process in sulphamate bath was studied.
The effects of process parameters, such as current density and
electrolyte composition, on the cathodic current efficiency,
microstructure, internal stress and mechanical properties were
investigated. Because of its crucial effect on the application to the
electroforming of microelectronic components, the development of
low internal stress coating with high leveling power was emphasized.
It was found that both the coating’s manganese content and the
cathodic current efficiency increased with the raise in current density.
In addition, the internal stress of the deposited coating showed
compressive nature at low current densities while changed to tensile
one at higher current densities. Moreover, the metallographic
observation, X-ray diffraction measurement, and polarization curve
measurement were conducted. It was found that the Ni-Mn coating
consisted of nano-sized columnar grains and the maximum hardness of
the coating was associated with (111) preferred orientation in the
microstructure. The grain size was refined along with the increase in
the manganese content of the coating, which accordingly, raised its
hardness and resistance to annealing softening. In summary, the
Ni-Mn coating prepared at lower current density of 1-2 A/dm2 had low
internal stress, high leveling power, and better corrosion resistance.
Abstract: The use of titanium fluoride and iron fluoride
(TiF3/FeF3) catalysts in combination with polutetrafluoroethylene
(PTFE) in plain zinc- dialkyldithiophosphate (ZDDP) oil is important
for the study of engine tribocomponents and is increasingly a strategy
to improve the formation of tribofilm and provide low friction and
excellent wear protection in reduced phosphorus plain ZDDP oil. The
influence of surface roughness and the concentration of
TiF3/FeF3/PTFE were investigated using bearing steel samples
dipped in lubricant solution at 100°C for two different heating time
durations. This paper addresses the effects of water drop contact
angle using different surface; finishes after treating them with
different lubricant combination. The calculated water drop contact
angles were analyzed using Design of Experiment software (DOE)
and it was determined that a 0.05 μm Ra surface roughness would
provide an excellent TiF3/FeF3/PTFE coating for antiwear resistance
as reflected in the Scanning electron microscopy (SEM) images and
the tribological testing under extreme pressure conditions. Both
friction and wear performance depend greatly on the PTFE/and
catalysts in plain ZDDP oil with 0.05 % phosphorous and on the
surface finish of bearing steel. The friction and wear reducing effects,
which was observed in the tribological tests, indicated a better micro
lubrication effect of the 0.05 μm Ra surface roughness treated at
100°C for 24 hours when compared to the 0.1 μm Ra surface
roughness with the same treatment.
Abstract: Crops diversity and maintaining and enhancing the
fertility of agricultural lands are basic principles of organic farming.
With a wider range of crops in agroecosystem can improve the ability
to control weeds, pests and diseases, and the performance of crops
rotation and food safety. In this sense, the main objective of the
research was to study the productivity and chemical composition of
some alternative crops and their adaptability to soil and climatic
conditions of the agricultural area in Southern Romania and to
cultivation in the organic farming system. The alternative crops were:
lentil (7 genotypes); five species of grain legumes (5 genotypes); four
species of oil crops (5 genotypes). The seed production was, on
average: 1343 kg/ha of lentil; 2500 kg/ha of field beans; 2400 kg/ha
of chick peas and blackeyed peas; more than 2000 kg/ha of atzuki
beans, over 1250 kg/ha of fenugreek; 2200 kg/ha of safflower; 570
kg/ha of oil pumpkin; 2150 kg/ha of oil flax; 1518 kg/ha of camelina.
Regarding chemical composition, lentil seeds contained: 22.18%
proteins, 3.03% lipids, 33.29% glucides, 4.00% minerals, and 259.97
kcal energy values. For field beans: 21.50% proteins, 4.40% lipids,
63.90% glucides, 5.85% minerals, 395.36 kcal energetic value. For
chick peas: 21.23% proteins, 4.55% lipids, 53.00% glucides, 3.67%
minerals, 348.22 kcal energetic value. For blackeyed peas: 23.30%
proteins, 2.10% lipids, 68.10% glucides, 3.93% minerals, 350.14 kcal
energetic value. For adzuki beans: 21.90% proteins, 2.60% lipids,
69.30% glucides, 4.10% minerals, 402.48 kcal energetic value. For
fenugreek: 21.30% proteins, 4.65% lipids, 63.83% glucides, 5.69%
minerals, 396.54 kcal energetic value. For safflower: 12.60%
proteins, 28.37% lipids, 46.41% glucides, 3.60% minerals, 505.78
kcal energetic value. For camelina: 20.29% proteins, 31.68% lipids,
36.28% glucides, 4.29% minerals, 526.63 kcal energetic value. For
oil pumpkin: 29.50% proteins, 36.92% lipids, 18.50% glucides,
5.41% minerals, 540.15 kcal energetic value. For oil flax: 22.56%
proteins, 34.10% lipids, 27.73% glucides, 5.25% minerals, 558.45
kcal energetic value.
Abstract: In this paper, we explore the macroeconomic effects
of the European Single Market on Austria by simulating the
McKibbin-Sachs Global Model. Global interdependences and the
impact of long-run effects on short-run adjustments are taken into
account. We study the sensitivity of the results with respect to
different assumptions concerning monetary and fiscal policies for the
countries and regions of the world economy. The consequences of
different assumptions about budgetary policies in Austria are also
investigated. The simulation results are contrasted with ex-post
evaluations of the actual impact of Austria’s membership in the
Single Market. As a result, it can be concluded that the Austrian
participation in the European Single Market entails considerable
long-run gains for the Austrian economy with nearly no adverse sideeffects
on any macroeconomic target variable.
Abstract: Neural activity in the human brain starts from the
early stages of prenatal development. This activity or signals
generated by the brain are electrical in nature and represent not only
the brain function but also the status of the whole body. At the
present moment, three methods can record functional and
physiological changes within the brain with high temporal resolution
of neuronal interactions at the network level: the
electroencephalogram (EEG), the magnet oencephalogram (MEG),
and functional magnetic resonance imaging (fMRI); each of these has
advantages and shortcomings. EEG recording with a large number of
electrodes is now feasible in clinical practice. Multichannel EEG
recorded from the scalp surface provides very valuable but indirect
information about the source distribution. However, deep electrode
measurements yield more reliable information about the source
locations intracranial recordings and scalp EEG are used with the
source imaging techniques to determine the locations and strengths of
the epileptic activity. As a source localization method, Low
Resolution Electro-Magnetic Tomography (LORETA) is solved for
the realistic geometry based on both forward methods, the Boundary
Element Method (BEM) and the Finite Difference Method (FDM). In
this paper, we review the findings EEG- LORETA about epilepsy.
Abstract: The reduction of phosphorus and sulfur in engine oil
are the main topics of this paper. Very reproducible boundary
lubrication tests were conducted as part of Design of Experiment
software (DOE) to study the behavior of fluorinated catalyst iron
fluoride (FeF3), and polutetrafluoroethylene or Teflon (PTFE) in
developing environmentally friendly (reduced P and S) anti-wear
additives for future engine oil formulations. Multi-component
Chevron fully formulated oil (GF3) and Chevron plain oil were used
with the addition of PTFE and catalyst to characterize and analyze
their performance. Lower phosphorus blends were the goal of the
model solution. Experiments indicated that new sub-micron FeF3
catalyst played an important role in preventing breakdown of the
tribofilm.
Abstract: Amoxicillin is an antibiotic which is widely used to
treat various infections in both human beings and animals. However,
when amoxicillin is released into the environment, it is a major
problem. Amoxicillin causes bacterial resistance to these drugs and
failure of treatment with antibiotics. Liquid membrane is of great
interest as a promising method for the separation and recovery of the
target ions from aqueous solutions due to the use of carriers for the
transport mechanism, resulting in highly selectivity and rapid
transportation of the desired metal ions. The simultaneous processes
of extraction and stripping in a single unit operation of liquid
membrane system are very interesting. Therefore, it is practical to
apply liquid membrane, particularly the HFSLM for industrial
applications as HFSLM is proved to be a separation process with
lower capital and operating costs, low energy and extractant with
long life time, high selectivity and high fluxes compared with solid
membranes. It is a simple design amenable to scaling up for industrial
applications. The extraction and recovery for (Amoxicillin) through
the hollow fiber supported liquid membrane (HFSLM) using
aliquat336 as a carrier were explored with the experimental data. The
important variables affecting on transport of amoxicillin viz.
extractant concentration and operating time were investigated. The
highest AMOX- extraction percentages of 85.35 and Amoxicillin
stripping of 80.04 were achieved with the best condition at 6 mmol/L
[aliquat336] and operating time 100 min. The extraction reaction
order (n) and the extraction reaction rate constant (kf) were found to
be 1.00 and 0.0344 min-1, respectively.
Abstract: The use of hydroelectric pump-storage system at large
scale, MW-size systems, is already widespread around the world.
Designed for large scale applications, pump-storage station can be
scaled-down for small, remote residential applications. Given the cost
and complexity associated with installing a substation further than
100 miles from the main transmission lines, a remote, independent
and self-sufficient system is by far the most feasible solution. This
article is aiming at the design of wind and solar power generating
system, by means of pumped-storage to replace the wind and /or solar
power systems with a battery bank energy storage. Wind and solar
pumped-storage power generating system can reduce the cost of
power generation system, according to the user's electricity load and
resource condition and also can ensure system reliability of power
supply. Wind and solar pumped-storage power generation system is
well suited for remote residential applications with intermittent wind
and/or solar energy. This type of power systems, installed in these
locations, could be a very good alternative, with economic benefits
and positive social effects. The advantage of pumped storage power
system, where wind power regulation is calculated, shows that a
significant smoothing of the produced power is obtained, resulting in
a power-on-demand system’s capability, concomitant to extra
economic benefits.
Abstract: Cerebellar ataxia is a steadily progressive
neurodegenerative disease associated with loss of motor control,
leaving patients unable to walk, talk, or perform activities of daily
living. Direct motor instruction in cerebella ataxia patients has limited
effectiveness, presumably because an inappropriate closed-loop
cerebellar response to the inevitable observed error confounds motor
learning mechanisms. Could the use of EEG based BCI provide
advanced biofeedback to improve motor imagery and provide a
“backdoor” to improving motor performance in ataxia patients? In
order to determine the feasibility of using EEG-based BCI control in
this population, we compare the ability to modulate mu-band power
(8-12 Hz) by performing a cued motor imagery task in an ataxia
patient and healthy control.
Abstract: We present a refined multiscale Shannon entropy for
analyzing electroencephalogram (EEG), which reflects the underlying
dynamics of EEG over multiple scales. The rationale behind
this method is that neurological signals such as EEG possess
distinct dynamics over different spectral modes. To deal with the
nonlinear and nonstationary nature of EEG, the recently developed
empirical mode decomposition (EMD) is incorporated, allowing a
decomposition of EEG into its inherent spectral components, referred
to as intrinsic mode functions (IMFs). By calculating the Shannon
entropy of IMFs in a time-dependent manner and summing them over
adaptive multiple scales, it results in an adaptive subscale entropy
measure of EEG. Simulation and experimental results show that
the proposed entropy properly reveals the dynamical changes over
multiple scales.
Abstract: The separation of Hg (II) from produced water by
hollow fiber contactors (HFC) was investigation. This system
included of two hollow fiber modules in the series connecting. The
first module used for the extraction reaction and the second module
for stripping reaction. Aliquat336 extractant was fed from the organic
reservoirs into the shell side of the first hollow fiber module and
continuous to the shell side of the second module. The organic liquid
was continuously feed recirculate and back to the reservoirs. The feed
solution was pumped into the lumen (tube side) of the first hollow
fiber module. Simultaneously, the stripping solution was pumped in
the same way in tube side of the second module. The feed and
stripping solution was fed which had a countercurrent flow. Samples
were kept in the outlet of feed and stripping solution at 1 hour and
characterized concentration of Hg (II) by Inductively Couple Plasma
Atomic Emission Spectroscopy (ICP-AES). Feed solution was
produced water from natural gulf of Thailand. The extractant was
Aliquat336 dissolved in kerosene diluent. Stripping solution used was
nitric acid (HNO3) and thiourea (NH2CSNH2). The effect of carrier
concentration and type of stripping solution were investigated.
Results showed that the best condition were 10 % (v/v) Aliquat336
and 1.0 M NH2CSNH2. At the optimum condition, the extraction and
stripping of Hg (II) were 98% and 44.2%, respectively.
Abstract: This paper reports a novel actuating design that uses
the shear deformation of a piezoelectric actuator to deflect a
bulge-diaphragm for driving an array microdroplet ejector. In essence,
we employed a circular-shaped actuator poled radial direction with
remnant polarization normal to the actuating electric field for inducing
the piezoelectric shear effect. The array microdroplet ejector consists
of a shear type piezoelectric actuator, a vibration plate, two chamber
plates, two channel plates and a nozzle plate. The vibration, chamber
and nozzle plate components are fabricated using nickel
electroforming technology, whereas the channel plate is fabricated by
etching of stainless steel. The diaphragm displacement was measured
by the laser two-dimensional scanning vibrometer. The ejected
droplets of the microejector were also observed via an optic
visualization system.
Abstract: The article presents a plasma chemical technology for
processing solid fuels, using examples of bituminous and brown
coals. Thermodynamic and experimental investigation of the
technology was made. The technology allows producing synthesis
gas from the coal organic mass and valuable components (technical
silicon, ferrosilicon, aluminum, and carbon silicon, as well as
microelements of rare metals, such as uranium, molybdenum,
vanadium, etc.) from the mineral mass. The thusly produced highcalorific
synthesis gas can be used for synthesis of methanol, as a
high-calorific reducing gas instead of blast-furnace coke as well as
power gas for thermal power plants.
Abstract: The problems arising from unbalanced data sets
generally appear in real world applications. Due to unequal class
distribution, many researchers have found that the performance of
existing classifiers tends to be biased towards the majority class. The
k-nearest neighbors’ nonparametric discriminant analysis is a method
that was proposed for classifying unbalanced classes with good
performance. In this study, the methods of discriminant analysis are
of interest in investigating misclassification error rates for classimbalanced
data of three diabetes risk groups. The purpose of this
study was to compare the classification performance between
parametric discriminant analysis and nonparametric discriminant
analysis in a three-class classification of class-imbalanced data of
diabetes risk groups. Data from a project maintaining healthy
conditions for 599 employees of a government hospital in Bangkok
were obtained for the classification problem. The employees were
divided into three diabetes risk groups: non-risk (90%), risk (5%),
and diabetic (5%). The original data including the variables of
diabetes risk group, age, gender, blood glucose, and BMI were
analyzed and bootstrapped for 50 and 100 samples, 599 observations
per sample, for additional estimation of the misclassification error
rate. Each data set was explored for the departure of multivariate
normality and the equality of covariance matrices of the three risk
groups. Both the original data and the bootstrap samples showed nonnormality
and unequal covariance matrices. The parametric linear
discriminant function, quadratic discriminant function, and the
nonparametric k-nearest neighbors’ discriminant function were
performed over 50 and 100 bootstrap samples and applied to the
original data. Searching the optimal classification rule, the choices of
prior probabilities were set up for both equal proportions (0.33: 0.33:
0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10)
and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples
indicated that the k-nearest neighbors approach when k=3 or k=4 and
the defined prior probabilities of non-risk: risk: diabetic as 0.90:
0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of
misclassification. The k-nearest neighbors approach would be
suggested for classifying a three-class-imbalanced data of diabetes
risk groups.
Abstract: This work proposes a data-driven multiscale based
quantitative measures to reveal the underlying complexity of
electroencephalogram (EEG), applying to a rodent model of
hypoxic-ischemic brain injury and recovery. Motivated by that real
EEG recording is nonlinear and non-stationary over different
frequencies or scales, there is a need of more suitable approach over
the conventional single scale based tools for analyzing the EEG data.
Here, we present a new framework of complexity measures
considering changing dynamics over multiple oscillatory scales. The
proposed multiscale complexity is obtained by calculating entropies of
the probability distributions of the intrinsic mode functions extracted
by the empirical mode decomposition (EMD) of EEG. To quantify
EEG recording of a rat model of hypoxic-ischemic brain injury
following cardiac arrest, the multiscale version of Tsallis entropy is
examined. To validate the proposed complexity measure, actual EEG
recordings from rats (n=9) experiencing 7 min cardiac arrest followed
by resuscitation were analyzed. Experimental results demonstrate that
the use of the multiscale Tsallis entropy leads to better discrimination
of the injury levels and improved correlations with the neurological
deficit evaluation after 72 hours after cardiac arrest, thus suggesting an
effective metric as a prognostic tool.
Abstract: Meeting the growth in demand for digital services
such as social media, telecommunications, and business and cloud
services requires large scale data centres, which has led to an increase
in their end use energy demand. Generally, over 30% of data centre
power is consumed by the necessary cooling overhead. Thus energy
can be reduced by improving the cooling efficiency. Air and liquid
can both be used as cooling media for the data centre. Traditional
data centre cooling systems use air, however liquid is recognised as a
promising method that can handle the more densely packed data
centres. Liquid cooling can be classified into three methods; rack heat
exchanger, on-chip heat exchanger and full immersion of the
microelectronics. This study quantifies the improvements of heat
transfer specifically for the case of immersed microelectronics by
varying the CPU and heat sink location. Immersion of the server is
achieved by filling the gap between the microelectronics and a water
jacket with a dielectric liquid which convects the heat from the CPU
to the water jacket on the opposite side. Heat transfer is governed by
two physical mechanisms, which is natural convection for the fixed
enclosure filled with dielectric liquid and forced convection for the
water that is pumped through the water jacket. The model in this
study is validated with published numerical and experimental work
and shows good agreement with previous work. The results show that
the heat transfer performance and Nusselt number (Nu) is improved
by 89% by placing the CPU and heat sink on the bottom of the
microelectronics enclosure.
Abstract: Previous studies on financial distress prediction choose
the conventional failing and non-failing dichotomy; however, the
distressed extent differs substantially among different financial
distress events. To solve the problem, “non-distressed”, “slightlydistressed”
and “reorganization and bankruptcy” are used in our article
to approximate the continuum of corporate financial health. This paper
explains different financial distress events using the two-stage method.
First, this investigation adopts firm-specific financial ratios, corporate
governance and market factors to measure the probability of various
financial distress events based on multinomial logit models.
Specifically, the bootstrapping simulation is performed to examine the
difference of estimated misclassifying cost (EMC). Second, this work
further applies macroeconomic factors to establish the credit cycle
index and determines the distressed cut-off indicator of the two-stage
models using such index. Two different models, one-stage and
two-stage prediction models are developed to forecast financial
distress, and the results acquired from different models are compared
with each other, and with the collected data. The findings show that the
one-stage model has the lower misclassification error rate than the
two-stage model. The one-stage model is more accurate than the
two-stage model.