Abstract: The paper presents the results of theoretical and
numerical modeling of propagation of shock waves in bubbly liquids
related to nonlinear effects (realistic equation of state, chemical
reactions, two-dimensional effects). On the basis on the Rankine-
Hugoniot equations the problem of determination of parameters of
passing and reflected shock waves in gas-liquid medium for
isothermal, adiabatic and shock compression of the gas component is
solved by using the wide-range equation of state of water in the
analitic form. The phenomenon of shock wave intensification is
investigated in the channel of variable cross section for the
propagation of a shock wave in the liquid filled with bubbles
containing chemically active gases. The results of modeling of the
wave impulse impact on the solid wall covered with bubble layer are
presented.
Abstract: In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals and then, selecting it for using with SPIHT codec. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MIT-BIH database. For assessing the functionality of the different multiwavelets in compressing ECG signals, in addition to known factors such as Compression Ratio (CR), Percent Root Difference (PRD), Distortion (D), Root Mean Square Error (RMSE) in compression literature, we also employed the Cross Correlation (CC) criterion for studying the morphological relations between the reconstructed and the original ECG signal and Signal to reconstruction Noise Ratio (SNR). The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation. After finding the most efficient multiwavelet, we apply SPIHT coding algorithm on the transformed signal by this multiwavelet.
Abstract: This paper and its companion (Part 2) deal with
modeling and optimization of two NP-hard problems in production
planning of flexible manufacturing system (FMS), part type selection
problem and loading problem. The part type selection problem and
the loading problem are strongly related and heavily influence the
system-s efficiency and productivity. The complexity of the problems
is harder when flexibilities of operations such as the possibility of
operation processed on alternative machines with alternative tools are
considered. These problems have been modeled and solved
simultaneously by using real coded genetic algorithms (RCGA)
which uses an array of real numbers as chromosome representation.
These real numbers can be converted into part type sequence and
machines that are used to process the part types. This first part of the
papers focuses on the modeling of the problems and discussing how
the novel chromosome representation can be applied to solve the
problems. The second part will discuss the effectiveness of the
RCGA to solve various test bed problems.
Abstract: Radio propagation from point-to-point is affected by
the physical channel in many ways. A signal arriving at a destination
travels through a number of different paths which are referred to as
multi-paths. Research in this area of wireless communications has
progressed well over the years with the research taking different
angles of focus. By this is meant that some researchers focus on
ways of reducing or eluding Multipath effects whilst others focus on
ways of mitigating the effects of Multipath through compensation
schemes. Baseband processing is seen as one field of signal
processing that is cardinal to the advancement of software defined
radio technology. This has led to wide research into the carrying out
certain algorithms at baseband. This paper considers compensating
for Multipath for Frequency Modulated signals. The compensation
process is carried out at Radio frequency (RF) and at Quadrature
baseband (QBB) and the results are compared. Simulations are
carried out using MatLab so as to show the benefits of working at
lower QBB frequencies than at RF.
Abstract: Physiological activity of the pineal gland with specific
responses in the reproductive territory may be interpreted by
monitoring the process parameters used in poultry practice in
different age batches of laying hens. As biological material were
used 105 laying hens, clinically healthy, belonging to ALBO SL-
2000 hybrid, raised on ground, from which blood samples were taken
at the age of 12 and 28 weeks. The haematological examinations
were concerned to obtain the total number of erythrocytes and
leukocytes and the main erythrocyte constant (RBC, PCV, MCV,
MCH, MCHC and WBC). The results allow the interpretation of the
reproductive status through the dynamics of the presented values.
Abstract: Wireless Sensor Network (WSN) comprises of sensor
nodes which are designed to sense the environment, transmit sensed
data back to the base station via multi-hop routing to reconstruct
physical phenomena. Since physical phenomena exists significant
overlaps between temporal redundancy and spatial redundancy, it is
necessary to use Redundancy Suppression Algorithms (RSA) for sensor
node to lower energy consumption by reducing the transmission
of redundancy. A conventional algorithm of RSAs is threshold-based
RSA, which sets threshold to suppress redundant data. Although
many temporal and spatial RSAs are proposed, temporal-spatial RSA
are seldom to be proposed because it is difficult to determine when
to utilize temporal or spatial RSAs. In this paper, we proposed a
novel temporal-spatial redundancy suppression algorithm, Codebookbase
Redundancy Suppression Mechanism (CRSM). CRSM adopts
vector quantization to generate a codebook, which is easily used to
implement temporal-spatial RSA. CRSM not only achieves power
saving and reliability for WSN, but also provides the predictability
of network lifetime. Simulation result shows that the network lifetime
of CRSM outperforms at least 23% of that of other RSAs.
Abstract: Sesame is one of the oldest and most important oil
crops as main crop and second crop agriculture. This study was
carried out to determine the effects of different inter- and intra-row
spacings on the yield and yield components on second crop sesame;
was set up in Antalya West Mediterranean Agricultural Research
Institue in 2009. Muganlı 57 sesame cultivar was used as plant
material. The field experiment was set up in a split plot design and
row spacings (30, 40, 50, 60 and 70 cm) were assigned to the main
plots and and intra-row spacings (5, 10, 20 and 30 cm) were assigned
to the subplots. Seed yield, oil ratio, oil yield, protein ratio and
protein yield were investigated. In general, wided inter row spacings
and intra-row spacings, resulted in decreased seed yield, oil yield and
protein yield. The highest seed yield, oil yield and protein yield
(respectively, 1115.0 kg ha-1, 551.3 kg ha-1, 224.7 kg ha-1) were
obtained from 30x5 cm plant density while the lowest seed yield, oil
yield and protein yield (respectively, 677.0 kg ha-1, 327.0 kg ha-1,
130.0 kg ha-1) were recorded from 70x30 cm plant density. As a
result, in terms of oil yield for second crop sesame agriculture, 30 cm
row spacing, and 5 cm intra row spacing are the most suitable plant
densities.
Abstract: Effective employee selection is a critical component
of a successful organization. Many important criteria for personnel
selection such as decision-making ability, adaptability, ambition, and
self-organization are naturally vague and imprecise to evaluate. The
rough sets theory (RST) as a new mathematical approach to
vagueness and uncertainty is a very well suited tool to deal with
qualitative data and various decision problems. This paper provides
conceptual, descriptive, and simulation results, concentrating chiefly
on human resources and personnel selection factors. The current
research derives certain decision rules which are able to facilitate
personnel selection and identifies several significant features based
on an empirical study conducted in an IT company in Iran.
Abstract: Traditional wind tunnel models are meticulously machined from metal in a process that can take several months. While very precise, the manufacturing process is too slow to assess a new design's feasibility quickly. Rapid prototyping technology makes this concurrent study of air vehicle concepts via computer simulation and in the wind tunnel possible. This paper described the Affects layer thickness models product with rapid prototyping on Aerodynamic Coefficients for Constructed wind tunnel testing models. Three models were evaluated. The first model was a 0.05mm layer thickness and Horizontal plane 0.1μm (Ra) second model was a 0.125mm layer thickness and Horizontal plane 0.22μm (Ra) third model was a 0.15mm layer thickness and Horizontal plane 4.6μm (Ra). These models were fabricated from somos 18420 by a stereolithography (SLA). A wing-body-tail configuration was chosen for the actual study. Testing covered the Mach range of Mach 0.3 to Mach 0.9 at an angle-of-attack range of -2° to +12° at zero sideslip. Coefficients of normal force, axial force, pitching moment, and lift over drag are shown at each of these Mach numbers. Results from this study show that layer thickness does have an effect on the aerodynamic characteristics in general; the data differ between the three models by fewer than 5%. The layer thickness does have more effect on the aerodynamic characteristics when Mach number is decreased and had most effect on the aerodynamic characteristics of axial force and its derivative coefficients.
Abstract: With the aim of improving nutritional profile and antioxidant capacity of gluten-free cookies, blueberry pomace, by-product of juice production, was processed into a new food ingredient by drying and grinding and used for a gluten-free cookie formulation. Since the quality of a baked product is highly influenced by the baking conditions, the objective of this work was to optimize the baking time and thickness of dough pieces, by applying Response Surface Methodology (RSM) in order to obtain the best technological quality of the cookies. The experiments were carried out according to a Central Composite Design (CCD) by selecting the dough thickness and baking time as independent variables, while hardness, color parameters (L*, a* and b* values), water activity, diameter and short/long ratio were response variables. According to the results of RSM analysis, the baking time of 13.74min and dough thickness of 4.08mm was found to be the optimal for the baking temperature of 170°C. As similar optimal parameters were obtained by previously conducted experiment based on sensory analysis, response surface methodology (RSM) can be considered as a suitable approach to optimize the baking process.
Abstract: The aim of the present study was to develop and
validate an inexpensive and simple high performance liquid
chromatographic (HPLC) method for the determination of colistin
sulfate. Separation of colistin sulfate was achieved on a ZORBAX
Eclipse XDB-C18 column using UV detection at λ=215 nm. The
mobile phase was 30 mM sulfate buffer (pH 2.5):acetonitrile(76:24).
An excellent linearity (r2=0.998) was found in the concentration
range of 25 - 400 μg/mL. Intra- day and inter-day precisions of
method (%RSD, n=3) were less than 7.9%.The developed and
validated method was applied to determination of the content of
colistin sulfate in medicated premix and animal feed sample.The
recovery of colistin from animal feed was satisfactorily ranged from
90.92 to 93.77%. The results demonstrated that the HPLC method
developed in this work is appropriate for direct determination of
colistin sulfate in commercial medicated premixes and animal feed.
Abstract: This paper describes a new method for extracting the fetal heart rate (fHR) and the fetal heart rate variability (fHRV) signal non-invasively using abdominal maternal electrocardiogram (mECG) recordings. The extraction is based on the fundamental frequency (Fourier-s) theorem. The fundamental frequency of the mother-s electrocardiogram signal (fo-m) is calculated directly from the abdominal signal. The heart rate of the fetus is usually higher than that of the mother; as a result, the fundamental frequency of the fetal-s electrocardiogram signal (fo-f) is higher than that of the mother-s (fo-f > fo-m). Notch filters to suppress mother-s higher harmonics were designed; then a bandpass filter to target fo-f and reject fo-m is implemented. Although the bandpass filter will pass some other frequencies (harmonics), we have shown in this study that those harmonics are actually carried on fo-f, and thus have no impact on the evaluation of the beat-to-beat changes (RR intervals). The oscillations of the time-domain extracted signal represent the RR intervals. We have also shown in this study that zero-to-zero evaluation of the periods is more accurate than the peak-to-peak evaluation. This method is evaluated both on simulated signals and on different abdominal recordings obtained at different gestational ages.
Abstract: Response Surface Methodology (RSM) is a powerful
and efficient mathematical approach widely applied in the
optimization of cultivation process. Cellulase enzyme production by
Trichoderma reesei RutC30 using agricultural waste rice straw and
banana fiber as carbon source were investigated. In this work,
sequential optimization strategy based statistical design was
employed to enhance the production of cellulase enzyme through
submerged cultivation. A fractional factorial design (26-2) was applied
to elucidate the process parameters that significantly affect cellulase
production. Temperature, Substrate concentration, Inducer
concentration, pH, inoculum age and agitation speed were identified
as important process parameters effecting cellulase enzyme synthesis.
The concentration of lignocelluloses and lactose (inducer) in the
cultivation medium were found to be most significant factors. The
steepest ascent method was used to locate the optimal domain and a
Central Composite Design (CCD) was used to estimate the quadratic
response surface from which the factor levels for maximum
production of cellulase were determined.
Abstract: This study fabricates p-type Ni1−xO:Li/n-Si heterojunction solar cells (P+/n HJSCs) by using radio frequency (RF) magnetron sputtering and investigates the effect of substrate temperature on photovoltaic cell properties. Grazing incidence x-ray diffraction, four point probe, and ultraviolet-visible-near infrared discover the optoelectrical properties of p-Ni1-xO thin films. The results show that p-Ni1-xO thin films deposited at 300 oC has the highest grain size (22.4 nm), average visible transmittance (~42%), and electrical resistivity (2.7 Ωcm). However, the conversion efficiency of cell is shown only 2.33% which is lower than the cell (3.39%) fabricated at room temperature. This result can be mainly attributed to interfacial layer thickness (SiOx) reduces from 2.35 nm to 1.70 nm, as verified by high-resolution transmission electron microscopy.
Abstract: During the last decade Panicum virgatum, known as
Switchgrass, has been broadly studied because of its remarkable
attributes as a substitute pasture and as a functional biofuel source.
The objective of this investigation was to establish soil suitability for
Switchgrass in the State of Mississippi. A linear weighted additive
model was developed to forecast soil suitability. Multicriteria
analysis and Sensitivity analysis were utilized to adjust and optimize
the model. The model was fit using seven years of field data
associated with soils characteristics collected from Natural Resources
Conservation System - United States Department of Agriculture
(NRCS-USDA). The best model was selected by correlating
calculated biomass yield with each model's soils-based output for
Switchgrass suitability. Coefficient of determination (r2) was the
decisive factor used to establish the 'best' soil suitability model.
Coefficients associated with the 'best' model were implemented
within a Geographic Information System (GIS) to create a map of
relative soil suitability for Switchgrass in Mississippi. A Geodatabase
associated with soil parameters was built and is available for future
Geographic Information System use.
Abstract: The absolute Cu atoms density in Cu(2S1/22P1/2)
ground state has been measured by Resonance Optical Absorption
(ROA) technique in a DC magnetron sputtering deposition with
argon. We measured these densities under variety of operation
conditions: pressure from 0.6 μbar to 14 μbar, input power from
10W to 200W and N2 mixture from 0% to 100%. For measuring the
gas temperature, we used the simulation of N2 rotational spectra
with a special computer code. The absolute number density of Cu
atoms decreases with increasing the N2 percentage of buffer gas at
any conditions of this work. But the deposition rate, is not decreased
with the same manner. The deposition rate variation is very small
and in the limit of quartz balance measuring equipment accuracy. So
we conclude that decrease in the absolute number density of Cu
atoms in magnetron plasma has not a big effect on deposition rate,
because the diffusion of Cu atoms to the chamber volume and
deviation of Cu atoms from direct path (towards the substrate)
decreases with increasing of N2 percentage of buffer gas. This is
because of the lower mass of N2 atoms compared to the argon ones.
Abstract: In this paper, a target signal detection method using
multiple signal classification (MUSIC) algorithm is proposed. The
MUSIC algorithm is a subspace-based direction of arrival (DOA)
estimation method. The algorithm detects the DOAs of multiple
sources using the inverse of the eigenvalue-weighted eigen spectra. To
apply the algorithm to target signal detection for GSC-based
beamforming, we utilize its spectral response for the target DOA in
noisy conditions. For evaluation of the algorithm, the performance of
the proposed target signal detection method is compared with that of
the normalized cross-correlation (NCC), the fixed beamforming, and
the power ratio method. Experimental results show that the proposed
algorithm significantly outperforms the conventional ones in receiver
operating characteristics(ROC) curves.
Abstract: Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.
Abstract: To investigate some relations between higher mathe¬matics scores in Chinese graduate student entrance examination and calculus (resp. linear algebra, probability statistics) scores in subject's completion examination of Chinese university, we select 20 students as a sample, take higher mathematics score as a decision attribute and take calculus score, linear algebra score, probability statistics score as condition attributes. In this paper, we are based on rough-set theory (Rough-set theory is a logic-mathematical method proposed by Z. Pawlak. In recent years, this theory has been widely implemented in the many fields of natural science and societal science.) to investigate importance of condition attributes with respective to decision attribute and strength of condition attributes supporting decision attribute. Results of this investigation will be helpful for university students to raise higher mathematics scores in Chinese graduate student entrance examination.
Abstract: Given a bivariate normal sample of correlated variables,
(Xi, Yi), i = 1, . . . , n, an alternative estimator of Pearson’s correlation
coefficient is obtained in terms of the ranges, |Xi − Yi|.
An approximate confidence interval for ρX,Y is then derived, and
a simulation study reveals that the resulting coverage probabilities
are in close agreement with the set confidence levels. As well, a
new approximant is provided for the density function of R, the
sample correlation coefficient. A mixture involving the proposed
approximate density of R, denoted by hR(r), and a density function
determined from a known approximation due to R. A. Fisher is shown
to accurately approximate the distribution of R. Finally, nearly exact
density approximants are obtained on adjusting hR(r) by a 7th degree
polynomial.