Abstract: In the Northern hemisphere, sheep reproduction is
seasonal (September-November). Among several natural factors
influencing the reproduction status of rams, we studied the daylight
length and temperature. Rams from different breeds were studied:
Merinos de Palas (half-precocious), Karakul de Botosani (halfbelated)
and Turcana (belated breed, low reproductive plasticity). In
Merinos de Palas, ejaculate volume during sexual repose is 51.3%
from normal quantity. When autumn climate was experimentally
induced, ejaculate volume reached 98.45% (Merinos), 94.97%
(Karakul) and 97.59% (Turcana). Semen density increased from
1.031-1.033 till 1.035 after exposition to artificial light and
temperature conditions. Spermatozoids mobility and sperm pH
improved, passing over 82% and 6.75, values identical to those in the
natural reproduction season. Behaviour analysis after
photoperiodicity indicated that over 83.3% Merinos and Karakul
males and all Turcana rams exteriorised normal and intense sexual
reflexes. Certain effort and reduced expenses brought rams in good
condition, producing higher quantity and quality sperm.
Abstract: Hydrodynamic pressures acting on upstream of concrete dams during an earthquake are an important factor in designing and assessing the safety of these structures in Earthquake regions. Due to inherent complexities, assessing exact hydrodynamic pressure is only feasible for problems with simple geometry. In this research, the governing equation of concrete gravity dam reservoirs with effect of fluid viscosity in frequency domain is solved and then compared with that in which viscosity is assumed zero. The results show that viscosity influences the reservoir-s natural frequency. In excitation frequencies near the reservoir's natural frequencies, hydrodynamic pressure has a considerable difference in compare to the results of non-viscose fluid.
Abstract: Investigations of the unimolecular decomposition of
vinyl ethyl ether (VEE), vinyl propyl ether (VPE) and vinyl butyl
ether (VBE) have shown that activation of the molecule of a ether
results in formation of a cyclic construction - the transition state (TS),
which may lead to the displacement of the thermodynamic
equilibrium towards the reaction products. The TS is obtained by
applying energy minimization relative to the ground state of an ether
under the program MM2 when taking into account the hydrogen bond
formation between a hydrogen atom of alkyl residue and the extreme
atom of carbon of the vinyl group. The dissociation of TS up to the
products is studied by energy minimization procedure using the
mathematical program Gaussian. The obtained calculation data for
VEE testify that the decomposition of this ether may be conditioned
by hydrogen bond formation for two possible versions: when α- or β-
hydrogen atoms of the ethyl group are bound to carbon atom of the
vinyl group. Applying the same calculation methods to other ethers
(VPE and VBE) it is shown that only in the case of hydrogen bonding
between α-hydrogen atom of the alkyl residue and the extreme atom
of carbon of the vinyl group (αH---C) results in decay of theses
ethers.
Abstract: Indium-tin oxide films are deposited by low plasma
temperature RF sputtering on highly flexible modification of glycol
polyethyleneterephtalate substrates. The produced layers are
characterized with transparency over 82 % and sheet resistance of
86.9 Ω/square. The film’s conductivity was further improved by
additional UV illumination from light source (365 nm), having power
of 250 W. The influence of the UV exposure dose on the structural
and electro-optical properties of ITO was investigated. It was
established that the optimum time of illumination is 10 minutes and
further UV treatment leads to polymer substrates degradation.
Structural and bonds type analysis show that at longer treatment
carbon atoms release and diffuse into ITO films, which worsen their
electrical behavior. For the optimum UV dose the minimum sheet
resistance was measured to be 19.2 Ω/square, and the maximum
transparency remained almost unchanged – above 82 %.
Abstract: The selection for plantation of a particular type of
mustard plant depending on its productivity (pod yield) at the stage
of maturity. The growth of mustard plant dependent on some
parameters of that plant, these are shoot length, number of leaves,
number of roots and roots length etc. As the plant is growing, some
leaves may be fall down and some new leaves may come, so it can
not gives the idea to develop the relationship with the seeds weight at
mature stage of that plant. It is not possible to find the number of
roots and root length of mustard plant at growing stage that will be
harmful of this plant as roots goes deeper to deeper inside the land.
Only the value of shoot length which increases in course of time can
be measured at different time instances. Weather parameters are
maximum and minimum humidity, rain fall, maximum and minimum
temperature may effect the growth of the plant. The parameters of
pollution, water, soil, distance and crop management may be
dominant factors of growth of plant and its productivity. Considering
all parameters, the growth of the plant is very uncertain, fuzzy
environment can be considered for the prediction of shoot length at
maturity of the plant. Fuzzification plays a greater role for
fuzzification of data, which is based on certain membership
functions. Here an effort has been made to fuzzify the original data
based on gaussian function, triangular function, s-function,
Trapezoidal and L –function. After that all fuzzified data are
defuzzified to get normal form. Finally the error analysis
(calculation of forecasting error and average error) indicates the
membership function appropriate for fuzzification of data and use to
predict the shoot length at maturity. The result is also verified using
residual (Absolute Residual, Maximum of Absolute Residual, Mean
Absolute Residual, Mean of Mean Absolute Residual, Median of
Absolute Residual and Standard Deviation) analysis.
Abstract: In this study, it is investigated the stability boundary of
Functionally Graded (FG) panel under the heats and supersonic
airflows. Material properties are assumed to be temperature
dependent, and a simple power law distribution is taken. First-order
shear deformation theory (FSDT) of plate is applied to model the
panel, and the von-Karman strain- displacement relations are
adopted to consider the geometric nonlinearity due to large
deformation. Further, the first-order piston theory is used to model the
supersonic aerodynamic load acting on a panel and Rayleigh damping
coefficient is used to present the structural damping. In order to find a
critical value of the speed, linear flutter analysis of FG panels is
performed. Numerical results are compared with the previous works,
and present results for the temperature dependent material are
discussed in detail for stability boundary of the panel with various
volume fractions, and aerodynamic pressures.
Abstract: The research was set up on chernozem soil at the Látókép AGTC MÉK research area of the University of Debrecen in Hungary. We examined the yield, the yield production per 1kg NPK fertilizer and the water and nutrient utilization of hybrid PR37N01 and PR37M81 in 2013. We found that PR37N01 produced the most yield at the level of N120+P (17,476kg ha-1) while PR37M81 reached the highest yield at level N150+PK (16,754kg ha-1). Studies related to yield production per 1kg NPK indicated that the best results were achieved at level N30+PK compared to the control treatment. Yield production per 1kg NPK was17.6kg kg-1 by P37N01 and 44.2kg kg-1 by PR37M81. By comparing the water utilization of hybrids we found that the worst water utilization results were reached in the control treatment (PR37N01: 26.2kg mm-1, PR37M81: 19.5kg mm-1). The best water utilization values were produced at level N120+PK in the case of hybrid PR37N01 (32.1kg mm-1) and at N150+PK in the case of hybrid PR37M81 (30.8kg mm-1). We established the values of the nutrient reaction and the fertilizer optimum of hybrids. We discovered a strong relationship between the amount of fertilizer applied and the yield produced (r2= 0.8228–0.9515). The best nutrient response was induced by hybrid PR37N01, while the weakest results were reached by hybrid PR37M81.
Abstract: Electromagnetic flow meter by measuring the varying of magnetic flux, which is related to the velocity of conductive flow, can measure the rate of fluids very carefully and precisely. Electromagnetic flow meter operation is based on famous Faraday's second Law. In these equipments, the constant magnetostatic field is produced by electromagnet (winding around the tube) outside of pipe and inducting voltage that is due to conductive liquid flow is measured by electrodes located on two end side of the pipe wall. In this research, we consider to 2-dimensional mathematical model that can be solved by numerical finite difference (FD) solution approach to calculate induction potential between electrodes. The fundamental concept to design the electromagnetic flow meter, exciting winding and simulations are come out by using MATLAB and PDE-Tool software. In the last stage, simulations results will be shown for improvement and accuracy of technical provision.
Abstract: In this era of technology, fueled by the pervasive usage of the internet, security is a prime concern. The number of new attacks by the so-called “bots", which are automated programs, is increasing at an alarming rate. They are most likely to attack online registration systems. Technology, called “CAPTCHA" (Completely Automated Public Turing test to tell Computers and Humans Apart) do exist, which can differentiate between automated programs and humans and prevent replay attacks. Traditionally CAPTCHA-s have been implemented with the challenge involved in recognizing textual images and reproducing the same. We propose an approach where the visual challenge has to be read out from which randomly selected keywords are used to verify the correctness of spoken text and in turn detect the presence of human. This is supplemented with a speaker recognition system which can identify the speaker also. Thus, this framework fulfills both the objectives – it can determine whether the user is a human or not and if it is a human, it can verify its identity.
Abstract: Noble metal participation in nanostructured
semiconductor catalysts has drawn much interest because of their
improved properties. Recently, it has been discussed by many
researchers that Ag participation in TiO2, CuO, ZnO semiconductors
showed improved photocatalytic and optical properties. In this
research, Ag/ZnO nanocomposite particles were prepared by
Ultrasonic Spray Pyrolysis(USP) Method. 0.1M silver and zinc
nitrate aqueous solutions were used as precursor solutions. The
Ag:Zn atomic ratio of the solution was selected 1:1. Experiments
were taken place under constant air flow of 400 mL/min at 800°C
furnace temperature. Particles were characterized by X-Ray
Diffraction (XRD), Scanning Electron Microscope (SEM) and
Energy Dispersive Spectroscopy (EDS). The crystallite sizes of Ag
and ZnO in composite particles are 24.6 nm, 19.7 nm respectively.
Although, spherical nanocomposite particles are in a range of 300-
800 nm, these particles are formed by the aggregation of primary
particles which are in a range of 20-60 nm.
Abstract: Several methods are available for weight and shape
optimization of structures, among which Evolutionary Structural
Optimization (ESO) is one of the most widely used methods. In ESO,
however, the optimization criterion is completely case-dependent.
Moreover, only the improving solutions are accepted during the
search. In this paper a Simulated Annealing (SA) algorithm is used
for structural optimization problem. This algorithm differs from other
random search methods by accepting non-improving solutions. The
implementation of SA algorithm is done through reducing the
number of finite element analyses (function evaluations).
Computational results show that SA can efficiently and effectively
solve such optimization problems within short search time.
Abstract: This paper presents an exact pruning algorithm with
adaptive pruning interval for general dynamic neural networks
(GDNN). GDNNs are artificial neural networks with internal dynamics.
All layers have feedback connections with time delays to the
same and to all other layers. The structure of the plant is unknown, so
the identification process is started with a larger network architecture
than necessary. During parameter optimization with the Levenberg-
Marquardt (LM) algorithm irrelevant weights of the dynamic neural
network are deleted in order to find a model for the plant as
simple as possible. The weights to be pruned are found by direct
evaluation of the training data within a sliding time window. The
influence of pruning on the identification system depends on the
network architecture at pruning time and the selected weight to be
deleted. As the architecture of the model is changed drastically during
the identification and pruning process, it is suggested to adapt the
pruning interval online. Two system identification examples show
the architecture selection ability of the proposed pruning approach.
Abstract: The paper deals with hydrodynamics of liquid-gas
layers under gas streaming through liquid layer on perforated plates
in column apparatuses. The plates with large apertures have been
investigated especially. It was shown that hydrodynamic regularities
for these plates are essentially different from known laws for foam
forming on fine-perforated plates. Main regularities of liquid-gas
interaction on plates with large apertures have been established.
Abstract: This paper presents an application of Artificial Neural Network (ANN) to forecast actual cost of a project based on the earned value management system (EVMS). For this purpose, some projects randomly selected based on the standard data set , and it is produced necessary progress data such as actual cost ,actual percent complete , baseline cost and percent complete for five periods of project. Then an ANN with five inputs and five outputs and one hidden layer is trained to produce forecasted actual costs. The comparison between real and forecasted data show better performance based on the Mean Absolute Percentage Error (MAPE) criterion. This approach could be applicable to better forecasting the project cost and result in decreasing the risk of project cost overrun, and therefore it is beneficial for planning preventive actions.
Abstract: Bangla Vowel characterization determines the spectral properties of Bangla vowels for efficient synthesis as well as recognition of Bangla vowels. In this paper, Bangla vowels in isolated word have been analyzed based on speech production model within the framework of Analysis-by-Synthesis. This has led to the extraction of spectral parameters for the production model in order to produce different Bangla vowel sounds. The real and synthetic spectra are compared and a weighted square error has been computed along with the error in the formant bandwidths for efficient representation of Bangla vowels. The extracted features produced good representation of targeted Bangla vowel. Such a representation also plays essential role in low bit rate speech coding and vocoders.
Abstract: In this paper we apply an Adaptive Network-Based
Fuzzy Inference System (ANFIS) with one input, the dependent
variable with one lag, for the forecasting of four macroeconomic
variables of US economy, the Gross Domestic Product, the inflation
rate, six monthly treasury bills interest rates and unemployment rate.
We compare the forecasting performance of ANFIS with those of the
widely used linear autoregressive and nonlinear smoothing transition
autoregressive (STAR) models. The results are greatly in favour of
ANFIS indicating that is an effective tool for macroeconomic
forecasting used in academic research and in research and application
by the governmental and other institutions
Abstract: Intrusion detection is a mechanism used to protect a
system and analyse and predict the behaviours of system users. An
ideal intrusion detection system is hard to achieve due to
nonlinearity, and irrelevant or redundant features. This study
introduces a new anomaly-based intrusion detection model. The
suggested model is based on particle swarm optimisation and
nonlinear, multi-class and multi-kernel support vector machines.
Particle swarm optimisation is used for feature selection by applying
a new formula to update the position and the velocity of a particle;
the support vector machine is used as a classifier. The proposed
model is tested and compared with the other methods using the KDD
CUP 1999 dataset. The results indicate that this new method achieves
better accuracy rates than previous methods.
Abstract: Let S be an ordered semigroup. In this paper we first introduce the concepts of (∈,∈ ∨q)-fuzzy ideals, (∈,∈ ∨q)-fuzzy bi-ideals and (∈,∈ ∨q)-fuzzy generalized bi-ideals of an ordered semigroup S, and investigate their related properties. Furthermore, we also define the upper and lower parts of fuzzy subsets of an ordered semigroup S, and investigate the properties of (∈,∈ ∨q)-fuzzy ideals of S. Finally, characterizations of regular ordered semigroups and intra-regular ordered semigroups by means of the lower part of (∈ ,∈ ∨q)-fuzzy left ideals, (∈,∈ ∨q)-fuzzy right ideals and (∈,∈ ∨q)- fuzzy (generalized) bi-ideals are given.
Abstract: This study presents a simulation model for converting coal to methanol, based on gasification technology with the commercial chemical process simulator, Pro/II® V8.1.1. The methanol plant consists of air separation unit (ASU), gasification unit, gas clean-up unit, and methanol synthetic unit. The clean syngas is produced with the first three operating units, and the model has been verified with the reference data from United States Environment Protection Agency. The liquid phase methanol (LPMEOHTM) process is adopted in the methanol synthetic unit. Clean syngas goes through gas handing section to reach the reaction requirement, reactor loop/catalyst to generate methanol, and methanol distillation to get desired purity over 99.9 wt%. The ratio of the total energy combined with methanol and dimethyl ether to that of feed coal is 78.5% (gross efficiency). The net efficiency is 64.2% with the internal power consumption taken into account, based on the assumption that the efficiency of electricity generation is 40%.
Abstract: In this paper, we introduce an effective strategy for
subgoal division and ordering based upon recursive subgoals and
combine this strategy with a genetic-based planning approach. This
strategy can be applied to domains with conjunctive goals. The main
idea is to recursively decompose a goal into a set of serializable
subgoals and to specify a strict ordering among the subgoals.
Empirical results show that the recursive subgoal strategy reduces the
size of the search space and improves the quality of solutions to
planning problems.