Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o

       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

The whole world and the Arab world, especially an important part of this international system, is undergoing a radical transformation at all levels. This mosaic of political, economic, social and military relations and alliances, whether based on the special interests of the major Powers or on the basis of mutual interests, The major transformations to social, economic, political and military conflict and these transformations still bear more surprises, at all levels, nothing remains constant, all changed, relations changed and alliances changed and loyalties fell and the principles of the M changed and the spectacular imperial economies collapsed and the will of the masses was no longer fixed.

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

     The radio drama is considered to be one of the arts that is discovered after a long period of theater's discovery. Initially , it was the broad framework of the theater's work when radio was broadcasting the shows on the huge theaters. This beginning encouraged many of the radio specialists to correlate plays with radio and make a novice and distinctive type of art. Thus, radio drama made its first step including the following   ( plays, short and long series drama as well as other types of radio arts). Because of the above mentioned , the researcher is stimulating  to study directing techniques to process the radio drama script ( Khata'a play as a sample).

The first chapter deals with the

When exercising their authority in the jurisprudence, judges are subject to a set of restrictions that they must adhere to, as they do not want their jurisprudence to be accepted and welcomed by law practitioners in general, and legal scholars in particular, and in contrast to it, the arrows of criticism and defamation will extend to that jurisprudence, and then they will have to reverse them . Perhaps the most important of those restrictions imposed on judges is their observance of justice between the parties to the lawsuit through their lack of bias for one of the parties at the expense of the other, in addition to their observance of public order and public morals, as well as their observance of the legal texts that they work under its u

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th