This study was conducted at glasshouse of Citrus and Tropical Research Department
in Tartus governorate, and Olive Nursery in Latakia governorate, during 2015 to
determine the influence of Indol-3-Butyric Acid (IBA) doses on hardwood and
softwood
top cuttings of three types of M. alba L. (B-1, B-5, KH-8) and three types
of M. nigra L. (M-4, KH-9, KH-1) and one fruitless type (B-3), which spreads
in different locations in Tartus, Syria. Hardwood cuttings were prepared during
February from one-year-old shoots, and the softwood top cuttings were prepared
during August in 2015. The cuttings were treated with different doses of IBA (1000,
2000 and 4000 ppm) in addition to the control application 0 ppm. The cuttings were
planted in the glasshouses in order to root.
In this research, We present a scientific advanced developed
study and keeping up with new studies and technologies of very
short-term electrical load forecasting and applying this study for
electrical load forecasting of basic Syrian electrical p
ower system
by studying this prediction for next four hours according to the
criterion applied in the Syrian Electricity Ministry with ten minutes
intervals ,we call it "Instant electrical load forecasting".
This research aims to produce a diagnosis system for breast cancer by using Neural
Network depending on Back Propagation algorithm(BPNN) and Adaptive Neuro Fuzzy
Inference System ‘ANFIS’, the both of studies was done using structural features of
b
iopsies in “Wisconson Breast Cancer “data base.
In the end a comparison was made between the two studies of malignant- benign
classification of breast masses of breast cancer which has accuracy 95,95% with BPNN
and 91.9% with ANFIS system, this results can be consider very important if they
compared with researches depending on image features that obtained of various devises
like mammography, magnetic resonance.
This research is based on experimental results of magnetization and magnetic susceptibility of ferrite slab prepared in a previous work with a computerized simulation to find the influence of ferrite slab on a microwave propagation in terms of determ
ining the behavior of attenuation factor .A slab of ferrite Co0.6Zn0.4Fe2O4were prepared by classical ceramic method. We have studied an influence of slab of the CoZn-ferrite its thickness is , loaded in a rectangular waveguide on a propagation of microwaves. The values of the reverse and forward attenuation factor has been found. After that, we choose the location of the slab X0 inside the guide which means the optimum status of microwave propagation has been reached at .
Evaporation is a major meteorological component of the hydrologic cycle, and it
plays an influential role in the development and management of water resources. The aim
of this study is to predict of the monthly pan evaporation in Homs meteostation
using
Artificial Neural Networks (ANNs), which based on monthly air temperature and relative
humidity data only as inputs, and monthly pan evaporation as output of the network. The
network was trained and verified using a back-propagation algorithm with different
learning methods, number of processing elements in the hidden layer(s), and the number of
hidden layers. Results shown good ability of (2-10-1) ANN to predict of monthly pan
evaporation with total correlation coefficient equals 96.786 % and root mean square error
equals 24.52 mm/month for the total data set. This study recommends using the artificial
neural networks approach to identify the most effective parameters to predict evaporation.
The contribution of our research include building an artificial neural
network in MATLAB program environment and improvement of
maximum loading point algorithm, to compute the most critical
voltage stability margin, for on-line voltage stability a
ssessment,
and a method to approximate the most critical voltage stability
margin accurately. a method to create a (ARTIFICIAL NEURAL
NETWORK) approach.
In this paper, we presented a scientific methodicalness in
very short term load forecasting depends on back propagation
artificial neural networks, and we relied upon real data of Syrian
electrical power system.
The method of vegetative propagation by hard wood cutting is considered of the
most important ones of prevalent and successful in its cultivation to obtain a Punica
Granatum seeding which are genetically uniform.
In this research,it was used three
categories fPunica Granatum
,Municipal,French,Darcoche,where they were taken the hard wood cutting of sound trees
which free of insecticides and fungal infections and bacteria, and divided into groups
which in cluded five deals to know the effect of hormone,stratification,impact,the hard
wood cutting age and its length on rooting.
It was found that the last three tested categories had no hormone effects on rooting.
The soft wood cutting of one year-old overtook the ones of two-years of age,where
they have the largest effect of rooting.The highest precentage of rooting and stronger were
at the length of 30 cm.
Its advised for stratification of the Municipal class befor its cultivation because it
increases the rooting percentage.
Darcoche is easy for rooting, because it roots by ahigh percentage if it had a
stratification or impact by the conditions of continuous wetting before cultivation.
The research presents a design for an automated checking system for students. The
system takes a picture of the student, then it extracts his/her basic facial features. The
network was trained using the reverse spreading algorithm. If a training da
tabase is
generated for each student consisting of 15 training samples contained of the necessary
facial expressions to identify the student for one time at the beginning of the semester, then
the neural network will be trained on students database to obtain a trained neural network
able to identify the students of each category depending on their physical appearance. That
will result in knowing who attends and who does not attend the session. The system
designed for this purpose was supplied with the trained network. The system provides the
possibility of automated checking for students according to the content of the study giving
the alarm in case of the existence of the picture of a student who does not belong to the
same group.
The concept of frequency reuse has been successfully implemented in modern cellular communications systems in order to increase the system capacity. Further improvement of capacity can be achieved by employing adaptive arrays at the base station. In
order to track the desired users, direction finding algorithms are used to locate the positions of mobile users as they move within or between cells.
Recently, neural networks-based direction finding algorithms have been supposed for source direction finding. The performance of neural network is evaluated by comparing their prediction, standard deviation and Mean Square Error (MSE) between their predicted and measurement values. The research depends on this context. So, it has been compared the antenna array output signals according to their amplitude, then selected the signal that has the best amplitude in the system’s final output.
