The cost of pile foundations is part of the super structure cost, and it became necessary to reduce this cost by studying the pile types then decision-making in the selection of the optimal pile type in terms of cost and time of production and quality .So The main objective of this study is to solve the time–cost–quality trade-off (TCQT) problem by finding an optimal pile type with the target of "minimizing" cost and time while "maximizing" quality. There are many types In the world of piles but  in this paper, the researcher proposed five pile types, one of them is not a traditional, and   developed a model for the problem and then employed particle swarm optimization (PSO) algorithm, as one of evolutionary algorithms with t

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

Biometrics is widely used with security systems nowadays; each biometric modality can be useful and has distinctive properties that provide uniqueness and ambiguity for security systems especially in communication and network technologies. This paper is about using biometric features of fingerprint, which is called (minutiae) to cipher a text message and ensure safe arrival of data at receiver end. The classical cryptosystems (Caesar, Vigenère, etc.) became obsolete methods for encryption because of the high-performance machines which focusing on repetition of the key in their attacks to break the cipher. Several Researchers of cryptography give efforts to modify and develop Vigenère cipher by enhancing its weaknesses.

In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in di

INTRODUCTION: A range of tools and technologies are at disposal for the purpose of defect detection. These include but are not limited to sensors, Statistical Process Control (SPC) software, Artificial Intelligence (AI) and machine learning (ML) algorithms, X-ray systems, ultrasound systems, and eddy current systems. OBJECTIVES: The determination of the suitable instrument or combination of instruments is contingent upon the precise production procedure and the category of flaw being identified. In certain cases, defects may necessitate real-time monitoring and analysis through the use of sensors and SPC software, whereas more comprehensive analysis may be required for other defects through the utilization of X-ray or ultrasound sy

The present research focuses on the study of the effect of mass transfer resistance on the rate of heat transfer in pool boiling. The nucleate pool boiling heat transfer coefficients for binary mixtures (ethanol-n-butanol, acetone-n-butanol, acetone-ethanol, hexane-benzene, hexane-heptane, and methanol-water) were measured at different concentrations of the more volatile components. The systems chosen covered a wide range of mixture behaviors.

The experimental set up for the present investigation includes electric heating element submerged in the test liquid mounted vertically. Thermocouple and a digital indictor measured the temperature of the heater surface. The actual heat transfer rate being obtained by multiplying the voltme

Arabian Political Regimes: Problems of Policies and Rule; An Introduction to Interpreting (The Arabian Spring) The Arab Region witnessed, since 2011, critical changes overthrew a group of Arab regimes in some of its countries, and the reaction of these changes are still going on up to now. These changes were given lots of justifications and interpretations. The current study tries to concentrate on the most important problems which were due to what was known as (The Arab Spring). The study proposes that the crisis which the countries of the area are exposed to is not spontaneous in many of its aspects. It is totally a crisis of rule and policies. Because it is a reflection of the nature of authority in the Arabian regimes on the one hand

Smart systems are the trend for modern organizations and should meet the quality of services that expect to produce. Internet of Everything (IoE) helped smart systems to adopt microcontrollers for improving the performance. Analyzing and controlling data in such a system are critical issues. In this study, a survey of IoE systems conducted to show how to apply a suitable model that meets such system requirements. The analysis of some microcontroller boards is explored based on known features. Factors for applying IoE devices have been defined such as connectivity, power consumption, compatibility, and cost. Different methods have been explained as an overview of applying IoE systems. Further, different approaches for applying IoE technology

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe