During the last few decades, many academic and professional groups gave attention to adopting the multi-criteria decision-making methods in a variety of contexts for decision-making that are given to the diversity and sophistication of their selections. Five different classification methods are tested and assessed in this paper. Each has its own set of five attribute selection approaches. By using the multi-criteria decision-making procedures, these data can be used to rate options. Technique for order of preference by similarity to ideal solution (TOPSIS) is designed utilizing a modified fuzzy analytic hierarchy process (MFAHP) to compute the weight alternatives for TOPSIS in order to obtain the confidence value of each class

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

Earthquakes occur on faults and create new faults. They also occur on  normal, reverse and strike-slip faults. The aim of this work is to suggest a new unified classification of Shallow depth earthquakes based on the faulting styles, and to characterize each class. The characterization criteria include the maximum magnitude, focal depth, b-constant value, return period and relations between magnitude, focal depth and dip of fault plane. Global Centroid Moment Tensor (GCMT) catalog is the source of the used data. This catalog covers the period from Jan.1976 to Dec. 2017. We selected only the shallow (depth less than 70kms) pure, normal, strike-slip and reverse earthquakes (magnitude ≥ 5) and excluded the oblique earthquakes. Th

    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

Inspite of the renovation and development that occurred on the

mathematics curricula and its teaching styles (methods), the teaching methods and the evaluation styles that the teachers of the country

follow  are  still  traditionaL It depends  on  the  normal distribution approach and the principle of individual differences among students in

addition the traditional tests that are used to evaluate student achievement are built on standard-referenced system. These types of tests focus on comparing the student's  performance with his peers'

performance. The limitary of this type of evaluation in diagnosing the

students'  acquisition  of  the  stu

          The aim of the present study is to formulate, evaluate and characterize the nanoemulsion of Domperidone a poorly water-soluble anti-emetic drug.

           Domperidone powder is white or almost white powder, photosensitive, practically insoluble in water, slightly soluble in ethanol and in methanol; soluble in dimethylformamide. It is used as an antiemetic for the short-term treatment of nausea and vomiting of various etiologies.

           Solubility studies were conducted to select the oil, surfactant and cosurfactant. Phase diagrams were constructed by aqueous phase

This paper aims to evaluate the reliability analysis for steel beam which represented by the probability of Failure and reliability index. Monte Carlo Simulation Method (MCSM) and First Order Reliability Method (FORM) will be used to achieve this issue. These methods need two samples for each behavior that want to study; the first sample for resistance (carrying capacity R), and second for load effect (Q) which are parameters for a limit state function. Monte Carlo method has been adopted to generate these samples dependent on the randomness and uncertainties in variables. The variables that consider are beam cross-section dimensions, material property, beam length, yield stress, and applied loads. Matlab software has be

The equation of Kepler is used to solve different problems associated with celestial mechanics and the dynamics of the orbit. It is an exact explanation for the movement of any two bodies in space under the effect of gravity. This equation represents the body in space in terms of polar coordinates; thus, it can also specify the time required for the body to complete its period along the orbit around another body. This paper is a review for previously published papers related to solve Kepler’s equation and eccentric anomaly. It aims to collect and assess changed iterative initial values for eccentric anomaly for forty previous years. Those initial values are tested to select the finest one based on the number of iterations, as well as the

It highlights the importance of construction projects because of its significant role in the development of society, including the buildings FEDE projects to their importance to raise the level of education through the conclusion of the special to implementation and the establishment of schools of contracts at the country level, which requires the completion of the project at less time and within the cost specified and the best quality and may highlight the importance of time on all the elements of what has an important role in setting up the project for various reasons may be the need for the use of schools as soon as possible, but the reality showed exceeded the completion of those schools could be up to 6 years and there are some cont