Abstract: Sensors possess several properties of physical
measures. Whether devices that convert a sensed signal into an
electrical signal, chemical sensors and biosensors, thus all these
sensors can be considered as an interface between the physical and
electrical equipment. The problem is the analysis of the multitudes of
saved settings as input variables. However, they do not all have the
same level of influence on the outputs. In order to identify the most
sensitive parameters, those that can guide users in gathering
information on the ground and in the process of model calibration
and sensitivity analysis for the effect of each change made.
Mathematical models used for processing become very complex.
In this paper a fuzzy rule-based system is proposed as a solution
for this problem. The system collects the available signals
information from sensors. Moreover, the system allows the study of
the influence of the various factors that take part in the decision
system. Since its inception fuzzy set theory has been regarded as a
formalism suitable to deal with the imprecision intrinsic to many
problems. At the same time, fuzzy sets allow to use symbolic models.
In this study an example was applied for resolving variety of
physiological parameters that define human health state. The
application system was done for medical diagnosis help. The inputs
are the signals expressed the cardiovascular system parameters, blood
pressure, Respiratory system paramsystem was done, it will be able
to predict the state of patient according any input values.
Abstract: The effect of varying holding temperature on hatching success, occurrence of deformities and mortality rates were investigated for goldlined seabream eggs. Wild broodstock (600 g) were stocked at a 2:1 male-female ratio in a 2 m3 fiberglass tank supplied with filtered seawater (37 g L-1 salinity, temp. range 24±0.5 oC [day] and 22±1 oC [night], DO2 in excess of 5.0mg L-1). Females were injected with 200 IU kg-1 HCG between 08.00 and 10.00 h and returned to tanks to spawn following which eggs were collected by hand using a 100μm net. Fertilized eggs at the gastrulation stage (120 L-1) were randomly placed into one of 12 experimental 6 L aerated (DO2 5 mg L-1) plastic containers with water temperatures maintained at 24±0.5 oC (ambient), 26±0.5 oC, 28± 0.5 oC and 30±0.5 oC using thermostats. Each treatment was undertaken in triplicate using a 12:12 photophase:scotophase photoperiod. No differences were recorded between eggs reared at 24 and 26 oC with respect to viability, deformity, mortality or unhatched egg rates. Increasing temperature reduced the number of viable eggs with those at 30 oC returning poorest performance (P < 0.05). Mortality levels were lowest for eggs incubated at 24 and 26 oC. The greatest level of deformities recorded was that for eggs reared at 28 oC.
Abstract: The choice of finite element to use in order to predict
nonlinear static or dynamic response of complex structures becomes
an important factor. Then, the main goal of this research work is to
focus a study on the effect of the in-plane rotational degrees of
freedom in linear and geometrically non linear static and dynamic
analysis of thin shell structures by flat shell finite elements. In this
purpose: First, simple triangular and quadrilateral flat shell finite
elements are implemented in an incremental formulation based on the
updated lagrangian corotational description for geometrically
nonlinear analysis. The triangular element is a combination of DKT
and CST elements, while the quadrilateral is a combination of DKQ
and the bilinear quadrilateral membrane element. In both elements,
the sixth degree of freedom is handled via introducing fictitious
stiffness. Secondly, in the same code, the sixth degrees of freedom in
these elements is handled differently where the in-plane rotational
d.o.f is considered as an effective d.o.f in the in-plane filed
interpolation. Our goal is to compare resulting shell elements. Third,
the analysis is enlarged to dynamic linear analysis by direct
integration using Newmark-s implicit method. Finally, the linear
dynamic analysis is extended to geometrically nonlinear dynamic
analysis where Newmark-s method is used to integrate equations of
motion and the Newton-Raphson method is employed for iterating
within each time step increment until equilibrium is achieved. The
obtained results demonstrate the effectiveness and robustness of the
interpolation of the in-plane rotational d.o.f. and present deficiencies
of using fictitious stiffness in dynamic linear and nonlinear analysis.
Abstract: Kombucha Tea Ferment (KT), was given to male
albino rats, (1ml/Kg of body weight), via gavages, during 2 weeks
before intraperitoneal administration of 3.5 mg/Kg body weight
CdCl2 and/or whole body γ-irradiation with 4Gy, and during 4 weeks
after each treatment. Hepatic and nephritic pathological changes
included significant increases of serum alanine transaminase (ALT),
aspartate transaminase (AST), and alkaline phosphatase (ALP)
activities, and creatinine and urea contents with significant decrease
in serum total antioxidant capacity (TAC). Increase in oxidative
stress markers in liver and kidney tissues expressed by significant
increase in malondialdehyde (MDA) and nitric oxide (NO) contents
associated to significant depletion in superoxide dismutase (SOD)
and catalase (CAT) activities, and reduced glutathione (GSH) content
were recorded. KT administration results in recovery of all the
pathological changes. It could be concluded that KT might protect
liver and kidney from oxidative damage induced by exposure to
cadmium and/ or γ-irradiation.
Abstract: In this study, the effects of biogas fuels on the performance of an annular micro gas turbine (MGT) were assessed experimentally and numerically. In the experiments, the proposed MGT system was operated successfully under each test condition; minimum composition to the fuel with the biogas was roughly 50% CH4 with 50% CO2. The power output was around 170W at 85,000 RPM as 90% CH4 with 10% CO2 was used and 70W at 65,000 RPM as 70% CH4 with 30% CO2 was used. When a critical limit of 60% CH4 was reached, the power output was extremely low. Furthermore, the theoretical Brayton cycle efficiency and electric efficiency of the MGT were calculated as 23% and 10%, respectively. Following the experiments, the measured data helped us identify the parameters of dynamic model in numerical simulation. Additionally, a numerical analysis of re-designed combustion chamber showed that the performance of MGT could be improved by raising the temperature at turbine inlet. This study presents a novel distributed power supply system that can utilize renewable biogas. The completed micro biogas power supply system is small, low cost, easy to maintain and suited to household use.
Abstract: In this paper we present a new method for over-height
vehicle detection in low headroom streets and highways using digital
video possessing. The accuracy and the lower price comparing to
present detectors like laser radars and the capability of providing
extra information like speed and height measurement make this
method more reliable and efficient. In this algorithm the features are
selected and tracked using KLT algorithm. A blob extraction
algorithm is also applied using background estimation and
subtraction. Then the world coordinates of features that are inside the
blobs are estimated using a noble calibration method. As, the heights
of the features are calculated, we apply a threshold to select overheight
features and eliminate others. The over-height features are
segmented using some association criteria and grouped using an
undirected graph. Then they are tracked through sequential frames.
The obtained groups refer to over-height vehicles in a scene.
Abstract: Partial combustion of biomass in the gasifier generates producer gas that can be used for heating purposes and as supplementary or sole fuel in internal combustion engines. In this study, the virgin biomass obtained from hingan shell is used as the feedstock for gasifier to generate producer gas. The gasifier-engine system is operated on diesel and on esters of vegetable oil of hingan in liquid fuel mode operation and then on liquid fuel and producer gas combination in dual fuel mode operation. The performance and emission characteristics of the CI engine is analyzed by running the engine in liquid fuel mode operation and in dual fuel mode operation at different load conditions with respect to maximum diesel savings in the dual fuel mode operation. It was observed that specific energy consumption in the dual fuel mode of operation is found to be in the higher side at all load conditions. The brake thermal efficiency of the engine using diesel or hingan oil methyl ester (HOME) is higher than that of dual fuel mode operation. A diesel replacement in the tune of 60% in dual fuel mode is possible with the use of hingan shell producer gas. The emissions parameters such CO, HC, NOx, CO2 and smoke are higher in the case of dual fuel mode of operation as compared to that of liquid fuel mode.
Abstract: Uranium mining and processing in Brazil occur in a
northeastern area near to Caetité-BA. Several Non-Governmental
Organizations claim that uranium mining in this region is a pollutant
causing health risks to the local population,but those in charge of the
complex extraction and production of“yellow cake" for generating
fuel to the nuclear power plants reject these allegations. This study
aimed at identifying potential problems caused by mining to the
population of Caetité. In this, work,the concentrations of 238U, 232Th
and 40K radioisotopes in the teeth of the Caetité population were
determined by ICP-MS. Teeth are used as bioindicators of
incorporated radionuclides. Cumulative radiation doses in the
skeleton were also determined. The concentration values were below
0.008 ppm, and annual effective dose due to radioisotopes are below
to the reference values. Therefore, it is not possible to state that the
mining process in Caetité increases pollution or radiation exposure in
a meaningful way.
Abstract: Spent petroleum catalyst from Korean petrochemical
industry contains trace amount of metals such as Ni, V and Mo.
Therefore an attempt was made to recover those trace metal using
bioleaching process. Different leaching parameters such as Fe(II)
concentration, pulp density, pH, temperature and particle size of
spent catalyst particle were studied to evaluate their effects on the
leaching efficiency. All the three metal ions like Ni, V and Mo
followed dual kinetics, i.e., initial faster followed by slower rate. The
percentage of leaching efficiency of Ni and V were higher than Mo.
The leaching process followed a diffusion controlled model and the
product layer was observed to be impervious due to formation of
ammonium jarosite (NH4)Fe3(SO4)2(OH)6. In addition, the lower
leaching efficiency of Mo was observed due to a hydrophobic coating
of elemental sulfur over Mo matrix in the spent catalyst.
Abstract: This paper describes the optimization of a complex
dairy farm simulation model using two quite different methods of
optimization, the Genetic algorithm (GA) and the Lipschitz
Branch-and-Bound (LBB) algorithm. These techniques have been
used to improve an agricultural system model developed by Dexcel
Limited, New Zealand, which describes a detailed representation of
pastoral dairying scenarios and contains an 8-dimensional parameter
space. The model incorporates the sub-models of pasture growth and
animal metabolism, which are themselves complex in many cases.
Each evaluation of the objective function, a composite 'Farm
Performance Index (FPI)', requires simulation of at least a one-year
period of farm operation with a daily time-step, and is therefore
computationally expensive. The problem of visualization of the
objective function (response surface) in high-dimensional spaces is
also considered in the context of the farm optimization problem.
Adaptations of the sammon mapping and parallel coordinates
visualization are described which help visualize some important
properties of the model-s output topography. From this study, it is
found that GA requires fewer function evaluations in optimization
than the LBB algorithm.
Abstract: Due to the environmental and price issues of current
energy crisis, scientists and technologists around the globe are
intensively searching for new environmentally less-impact form of
clean energy that will reduce the high dependency on fossil fuel.
Particularly hydrogen can be produced from biomass via thermochemical
processes including pyrolysis and gasification due to the
economic advantage and can be further enhanced through in-situ
carbon dioxide removal using calcium oxide. This work focuses on
the synthesis and development of the flowsheet for the enhanced
biomass gasification process in PETRONAS-s iCON process
simulation software. This hydrogen prediction model is conducted at
operating temperature between 600 to 1000oC at atmospheric
pressure. Effects of temperature, steam-to-biomass ratio and
adsorbent-to-biomass ratio were studied and 0.85 mol fraction of
hydrogen is predicted in the product gas. Comparisons of the results
are also made with experimental data from literature. The
preliminary economic potential of developed system is RM 12.57 x
106 which equivalent to USD 3.77 x 106 annually shows economic
viability of this process.
Abstract: With major technological advances and to reduce the
cost of training apprentices for real-time critical systems, it was
necessary the development of Intelligent Tutoring Systems for
training apprentices in these systems. These systems, in general, have
interactive features so that the learning is actually more efficient,
making the learner more familiar with the mechanism in question. In
the home stage of learning, tests are performed to obtain the student's
income, a measure on their use. The aim of this paper is to present a
framework to model an Intelligent Tutoring Systems using the UML
language. The various steps of the analysis are considered the
diagrams required to build a general model, whose purpose is to
present the different perspectives of its development.
Abstract: Information regarding early onset neonatal sepsis
(EONS) pathogens may vary between regions. Global perspectives
showed Group B Streptococcal (GBS) as the most common causative
pathogens, but the widespread use of intrapartum antibiotics has
changed the pathogens pattern towards gram negative
microorganisms, especially E. coli. Objective of this study is to
describe the pathogens isolated, to assess current treatment and risk
of EONS. Records of 899 neonates born in three General Hospitals
between 2009 until 2012 were retrospectively reviewed. Proven was
found in 22 (3%) neonates. The majority was isolated with gram
positive organisms, 17 (2.3%). All grams positive and most gram
negative organisms showed sensitivity to the tested antibiotics. Only
two rare gram negative organisms showed total resistant. Male was
possible risk of proven EONS. Although proven EONS remains
uncommon in Malaysia, nonetheless, the effect of intrapartum
antibiotics still required continuous surveillance.
Abstract: In a world worried about water resources with the
shadow of drought and famine looming all around, the quality of
water is as important as its quantity. The source of all concerns is the
constant reduction of per capita quality water for different uses.
Iran With an average annual precipitation of 250 mm compared to
the 800 mm world average, Iran is considered a water scarce country
and the disparity in the rainfall distribution, the limitations of
renewable resources and the population concentration in the margins
of desert and water scarce areas have intensified the problem.
The shortage of per capita renewable freshwater and its poor
quality in large areas of the country, which have saline, brackish or
hard water resources, and the profusion of natural and artificial
pollutant have caused the deterioration of water quality.
Among methods of treatment and use of these waters one can refer
to the application of membrane technologies, which have come into
focus in recent years due to their great advantages. This process is
quite efficient in eliminating multi-capacity ions; and due to the
possibilities of production at different capacities, application as
treatment process in points of use, and the need for less energy in
comparison to Reverse Osmosis processes, it can revolutionize the
water and wastewater sector in years to come. The article studied the
different capacities of water resources in the Persian Gulf and Oman
Sea watershed basins, and processes the possibility of using
nanofiltration process to treat brackish and non-conventional waters
in these basins.
Abstract: This paper illustrates the use of a combined neural
network model for classification of electrocardiogram (ECG) beats.
We present a trainable neural network ensemble approach to develop
customized electrocardiogram beat classifier in an effort to further
improve the performance of ECG processing and to offer
individualized health care.
We process a three stage technique for detection of premature
ventricular contraction (PVC) from normal beats and other heart
diseases. This method includes a denoising, a feature extraction and a
classification. At first we investigate the application of stationary
wavelet transform (SWT) for noise reduction of the
electrocardiogram (ECG) signals. Then feature extraction module
extracts 10 ECG morphological features and one timing interval
feature. Then a number of multilayer perceptrons (MLPs) neural
networks with different topologies are designed.
The performance of the different combination methods as well as
the efficiency of the whole system is presented. Among them,
Stacked Generalization as a proposed trainable combined neural
network model possesses the highest recognition rate of around 95%.
Therefore, this network proves to be a suitable candidate in ECG
signal diagnosis systems. ECG samples attributing to the different
ECG beat types were extracted from the MIT-BIH arrhythmia
database for the study.
Abstract: Due to the deregulation of the Electric Supply
Industry and the resulting emergence of electricity market, the
volumes of power purchases are on the rise all over the world. In a
bid to meet the customer-s demand in a reliable and yet economic
manner, utilities purchase power from the energy market over and
above its own production. This paper aims at developing an optimal
power purchase model with two objectives viz economy and
environment ,taking various functional operating constraints such as
branch flow limits, load bus voltage magnitudes limits, unit capacity
constraints and security constraints into consideration.The price of
purchased power being an uncertain variable is modeled using fuzzy
logic. DEMO (Differential Evolution For Multi-objective
Optimization) is used to obtain the pareto-optimal solution set of the
multi-objective problem formulated. Fuzzy set theory has been
employed to extract the best compromise non-dominated solution.
The results obtained on IEEE 30 bus system are presented and
compared with that of NSGAII.
Abstract: The clustering ensembles combine multiple partitions
generated by different clustering algorithms into a single clustering
solution. Clustering ensembles have emerged as a prominent method
for improving robustness, stability and accuracy of unsupervised
classification solutions. So far, many contributions have been done to
find consensus clustering. One of the major problems in clustering
ensembles is the consensus function. In this paper, firstly, we
introduce clustering ensembles, representation of multiple partitions,
its challenges and present taxonomy of combination algorithms.
Secondly, we describe consensus functions in clustering ensembles
including Hypergraph partitioning, Voting approach, Mutual
information, Co-association based functions and Finite mixture
model, and next explain their advantages, disadvantages and
computational complexity. Finally, we compare the characteristics of
clustering ensembles algorithms such as computational complexity,
robustness, simplicity and accuracy on different datasets in previous
techniques.
Abstract: In this study, the designed dual stage membrane
bioreactor (MBR) system was conceptualized for the treatment of
cyanide and heavy metals in electroplating wastewater. The design
consisted of a primary treatment stage to reduce the impact of
fluctuations and the secondary treatment stage to remove the residual
cyanide and heavy metal contaminants in the wastewater under
alkaline pH conditions. The primary treatment stage contained
hydrolyzed Citrus sinensis (C. sinensis) pomace and the secondary
treatment stage contained active Aspergillus awamori (A. awamori)
biomass, supplemented solely with C. sinensis pomace extract from
the hydrolysis process. An average of 76.37%, 95.37%, 93.26 and
94.76% and 99.55%, 99.91%, 99.92% and 99.92% degradation
efficiency for total cyanide (T-CN), including the sorption of nickel
(Ni), zinc (Zn) and copper (Cu) were observed after the first and
second treatment stages, respectively. Furthermore, cyanide
conversion by-products degradation was 99.81% and 99.75 for both
formate (CHOO-) and ammonium (NH4
+) after the second treatment
stage. After the first, second and third regeneration cycles of the C.
sinensis pomace in the first treatment stage, Ni, Zn and Cu removal
achieved was 99.13%, 99.12% and 99.04% (first regeneration cycle),
98.94%, 98.92% and 98.41% (second regeneration cycle) and 98.46
%, 98.44% and 97.91% (third regeneration cycle), respectively.
There was relatively insignificant standard deviation detected in all
the measured parameters in the system which indicated
reproducibility of the remediation efficiency in this continuous
system.
Abstract: Orthogonal Frequency Division Multiplexing
(OFDM) is an efficient method of data transmission for high speed
communication systems. However, the main drawback of OFDM
systems is that, it suffers from the problem of high Peak-to-Average
Power Ratio (PAPR) which causes inefficient use of the High Power
Amplifier and could limit transmission efficiency. OFDM consist of
large number of independent subcarriers, as a result of which the
amplitude of such a signal can have high peak values. In this paper,
we propose an effective reduction scheme that combines DCT and
SLM techniques. The scheme is composed of the DCT followed by
the SLM using the Riemann matrix to obtain phase sequences for the
SLM technique. The simulation results show PAPR can be greatly
reduced by applying the proposed scheme. In comparison with
OFDM, while OFDM had high values of PAPR –about 10.4dB our
proposed method achieved about 4.7dB reduction of the PAPR with
low complexities computation. This approach also avoids
randomness in phase sequence selection, which makes it simpler to
decode at the receiver. As an added benefit, the matrices can be
generated at the receiver end to obtain the data signal and hence it is
not required to transmit side information (SI).
Abstract: Determination of nano particle size is substantial since
the nano particle size exerts a significant effect on various properties
of nano materials. Accordingly, proposing non-destructive, accurate
and rapid techniques for this aim is of high interest. There are some
conventional techniques to investigate the morphology and grain size
of nano particles such as scanning electron microscopy (SEM),
atomic force microscopy (AFM) and X-ray diffractometry (XRD).
Vibrational spectroscopy is utilized to characterize different
compounds and applied for evaluation of the average particle size
based on relationship between particle size and near infrared spectra
[1,4] , but it has never been applied in quantitative morphological
analysis of nano materials. So far, the potential application of nearinfrared
(NIR) spectroscopy with its ability in rapid analysis of
powdered materials with minimal sample preparation, has been
suggested for particle size determination of powdered
pharmaceuticals. The relationship between particle size and diffuse
reflectance (DR) spectra in near infrared region has been applied to
introduce a method for estimation of particle size. Back propagation
artificial neural network (BP-ANN) as a nonlinear model was applied
to estimate average particle size based on near infrared diffuse
reflectance spectra. Thirty five different nano TiO2 samples with
different particle size were analyzed by DR-FTNIR spectrometry and
the obtained data were processed by BP- ANN.