The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

Evaluation of Dot. ELISA test for Diagnosis Visceral Leishmaniasis in Infected Children

That the child in the early years of his life learns a lot of experiences that help him
grow properly, and if the availability of the child family atmosphere full of love and affection
and trust he was able to grow healthy growth and is in accordance with itself and with the
community in which they live, and stop method of the child in the expression of fear on the
nature of situation and on the theme of fear and the reaction of those around the child as well
as the vague positions that can not a child from its interpretation raises his fear, and its lead in
life are the kindergarten of the growing concerns him, causing his social concern, therefore,
targeted current research to identify patterns of parental care(mot

  For the first time in Iraq, this study was conducted to evaluate the usefulness of Dot.ELISA, for detecting anti - Leishmania donovani antibodies in serum samples from suspected patient  (children under 8 years ) with Visceral Leishmaniasis V.L..  Sera from 73 V.L. , 60 Healthy controls, and 57   patient with other parasitic diseases other than V.L. (Amoebiasis, Giardiasis , Toxoplasmosis, Schistosomiasis , Hydatidosis, Ascariasis , Lupus Erythromatosus , Viral Hepatitis, and Cutaneous Leishmaniasis) were examined. Anti Leishmania donovani antibodies detected  in 71 out of 73  suspected Visceral Leishmaniasis . Data of this study showed that infection in male group was more than female group. Result o

Abstract:
The current research aims to distinguish the talent for the kindergarten
children and its relation with some changes . The research included ( 170 )
child (male , female ) from the kindergarten children on the year 2009 – 2010
the researcher had used PRED meter to achieve the goals of this research
after being sure from the honesty and the prove and the ( person ) connection
coefficient had been used to discover the relation between the talent and the
changes which had been mentioned in the research . The result proved that
the children had talents the toys and the educational scientifically scholarship
finally the researcher had presented some recommendations and suggestions
for other studies .<

It is certain that marriage has the favor of the continuity of human kind since the Prophet Adam till now. But this important event is threatened by some justifications which lead to its delay or abandonment. In the West, sexual relations, illegal friendships, and disrespect of marriage sacredness lead to this delay. While the reasons behind the delay of marriage in the Arab world refer to high dowries, women go out to work, and the religious and scientific ignorance of the need and importance of marriage. The problem also differs according to the difference between the rural and urban regions. On one hand, we find that early marriage is a necessity in the rural regions; on the other hand, the delay of marriage is a clear and nat

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne