The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

Produced water is accompanied with the production of oil and gas especially at the fields producing by water drive or water injection. The quantity of these waters is expected to be more complicated problem with an increasing in water cut which is expected to be 3-8 barrels water/produced barrel oil.Produced water may contain many constituents based on what is present in the subsurface at a particular location. Produced water contains dissolved solids and hydrocarbons (dissolved and suspended) and oxygen depletion. The most common dissolved solid is salt with concentrations range between a few parts per thousand to hundreds parts per thousand. In addition to salt, many produced waters also contain high levels of heavy metals like zinc, bari

Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t

Abstract

The research aims at achieving a set of objectives, which is to study a vital variable in the organizations which is the talent management and its impact on encouraging and empowering employees to take part in making appropriate decisions with their heads in the Iraqi Cement State Company. The problem of this research is in finding solutions to the weaknesses that face the managers in attracting talented employees and keep them in the company, and this leads to a weak capacity of the company on authorizing talented employees and giving them the needed confidence to participate in decision making process. The research sample was included (45) managers in the researched company. Th

All domains in this world built based on set of theories. Those theories have been responsible for interpretation of some phenomena and interlocking relationships around us. Commonly, theories are categorized by which aspect is believed. Also,can find a group of theories produced regardingto the leadership domain. This paper will be presented some of these theories like (Great Man Theory, Trait Theory, Behavioral Theories, Contingency Theories, Situational Theory, Transactional Theories, and Transformational Theories). where these theories considered the most popular and common in the field of leader and will be discussed by this work

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f