Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

The Islamic architectural heritage constitutes a civilized fortune that has to be preserved and protected and work should be done to maintain its development to be more convenient for the circumstances of the age and the civilization transformations. Due to the fact that architecture represents the civilization pot and cultural identity, its originality has to be preserved and work has to be done to prevent the strange architectural invasion that changes its character and make it lose the identity and the character and detached from its roots and environment.    

Decoration, in the interior design, as a concept is connected to ornamentation process of interior spaces, which is a process of adding certain items

      The problem of multi assembly line balancing appears as one of the most prominent and complex type of problem. The research problem of this dissertation is concerned with choosing the suitable method that includes the nature of the processes of the multi assembly type of the sewing line at factory no. (7). The State Company for Leather Manufacturing. The sewing line currently suffers from idle times at work stations which resulted in low production levels that do not meet the production plans. The authors have devised a flexible simulation model which uses the uniform distribution to generate task time for each shoe type produced by the factory. The simulation of the multi assembly line was based on assigni

The research aims to identify the factors that affect the quality of the product by using the Failure Mode and Effect Analysis (FMEA) tool and to suggest measures to reduce the deviations or defects in the production process. I used the case study approach to reach its goals, and the air filter product line was chosen in the air filters factory of Al-Zawraa General Company. The research sample was due to the emergence of many defects of different impact and the continuing demand for the product. I collected data and information from the factory records for two years (2018-2019) and used a scheme Pareto Fishbone Diagram as well as an FMEA tool to analyze data and generate results.

Par

Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

The research Reviews the sides of highlight importance of the Nano-Accounting which doing the accounting performance functions fully computerized without the intervention of an accountant, to solve the problem of not keeping up the  rationalization of recording and accounting systems, with the rationalization of production which fully computerized.(be invisible and hidden accounting), resulting by linking or interaction of the accounting, additive production system represented three-dimensional printers, open source and recycling. That which result the rationalizing the facilities of production, organization and self-control which derived nanotechnology idea, which aims to minimize materials and change it properties, then view the a

The researchers seek to shed light on the importance of accounting disclosure on social responsibility, and the research aims to provide a theoretical approach to social accounting and its disclosure, identify the concept of sustainable development, highlight the theoretical foundations of sustainable development and employ disclosure of social responsibility towards achieving the goals of sustainable development, and identify the impact of The accounting disclosure on social responsibility in achieving sustainable development goals, and the research problem can be reviewed by asking the following question (Does the accounting disclosure of the social responsibility of economic units contribute to achieving sustainable developmen

The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al