Alkut university college journal

The phenomenon of unemployment is one of the most prominent economic and social challenges facing the process of growth and development of the Iraqi economy, which is related to a set of economic variables, whether in terms of influence or influence, and thus unemployment is one of the important topics that must be focused on, studying and analyzing the economic variables affecting them, From here the research sought to know the impact of some economic variables represented (the rate of growth of the gross domestic product, the growth rate of current spending, the rate of growth of investment spending, the rate of inflation, and the formation of public and private capital) on the unemployment rate in Iraq during the period (2004-2017), Through the use of multiple linear regression analysis. To assess the ability and effectiveness of economic variables in affecting the unemployment rate in Iraq, Some conclusions were reached, and appropriate recommendations were made to create job opportunities and alleviate or reduce the unemployment problem.

The aim of this research is to know the non-deposit funding sources and their impact on the profitability of Iraqi commercial banks for the period (2009-2018), as they represent the lifeblood of these banks because they have a direct and actual impact on their performance, and the fact that non-deposit funding sources have become important in financial studies. Therefore, it was necessary to address them and demonstrate their importance in this research, and the research methodology consisted of the inductive approach and the quantitative standard method to reach more accurate results using the statistical program ((EVIEWS 10), where the behavior of the dependent variable (profitability) was studied measured by the rate of return on assets (ROA), the rate of return on equity (ROE), and the independent variables (non-depositary funding sources) represented by creditors and allocations. To achieve this, a model was built to estimate the relationship between the independent variables and the dependent variables based on the Panel Data model. Several results were reached, the most important of which is the existence of a positive and significant relationship between creditors and profitability measured by the rate of return on assets (ROA) and the rate of return on equity (ROE), and the presence of an inverse significant relationship between allocations and profitability measured by the rate of return on assets (ROA) and return on rights. The researcher also recommends the necessity to diversify the sources of funding in order to distribute the risks that commercial banks in Iraq may be exposed to in general and the commercial banks (the research sample) in particular, the most important of which is the risk of liquidity shortage, which increases their profitability, and commercial banks should take advantage of opportunities. In an optimal way to attract non-depositary funding sources and invest them in a way that raises the profitability index of commercial banks in Iraq.

The management of foreign reserves in a manner that ensures the adequacy of these assets, which must be at the disposal of the economic authority in order to achieve a specific set of goals, and that it has a great role that can be used in addressing economic problems, whether directly or indirectly in the Iraqi economy. As well as the contribution of the capital and financial account. Foreign reserves have feasibility and effectiveness in their impact on the Iraqi economy by raising the exchange rate, defending it, achieving harmonization between the benefits achieved from them and the costs involved in maintaining them, and achieving a balance in the balance of payments and financing the state's general budget and that the optimal levels of foreign reserves that the state can maintain In light of the available investment opportunities and self-insurance against external shocks in Iraq in light of fluctuations in oil price.

Classification is a significant technique for data mining with wide applications to identify the different categories of data used in virtually every area in our lives. Classification is used to label the individual in relation to the predefined groups according to the characteristics of the individual. This paper sheds light on performance appraisal based on (precision, Recall, F-measure) data classification analysis using a classification algorithm (LogitBoost and Naïve Bay). The Naïve Bayes, algorithm, is based on probability and the LogitBoost algorithm is based on the finding that Adaboost basically matches the training data using an additive logistic regression model. The paper sets out, to render comparative analyses of Naive Bayes and LogitBoost classifiers in the context of job classification dataset, Experimental results revealed that LogitBoost has highest result in (precision = 82.73 percent, recall = 83.33 percent, F-measure = 82.31 percent) compared to the Naive bayes algorithm for the data set mentioned above.

Wireless technologies are rapidly being adapted from simple monitoring and control to supervisory control and data acquisition (SCADA) systems. Wireless provides highly reliable data communications in the hard and interference-heavy conditions. In this article, a new wireless SCADA system has been built to control the electrostatic precipitator (ESP) in Al-Tahady site/Al-Zawraa state company wirelessly. Two wireless devices are used Rocket M5 and AirLive_WHA-5500CPE which utilize the Wi-Fi wireless technology and the IEEE802.11/b standard was used. They used as a transceiver for sending and receiving the information between the master station (MS) and Programming Logic Controller (PLC). A more detailed focus on Iraq cement plants using wireless technologies for monitoring and control of the whole process as an application also was presented.

Machine learning algorithms have been a hallmark of data mining in image and signal processing. Several studies have proposed various methods for improving classification accuracy. Artificial Neural network (ANN) is one of the most important data mining classification method among predictive algorithms. The performance of ANN is affected by several parameters such as a number of hidden layers neurons, learning function, stop conditions and network architecture. Parameter regulation is a point of critical challenge in this algorithm. The main purpose of this study is to provide a novel approach by using multi-objective genetic algorithm and ensemble classifier to obtain optimal parameters of ANN. To this end, first, a set of neural networks were trained by setting their parameters through the multi-objective genetic algorithm. Next, the best combination of neural networks was selected to make an ensemble classifier. This method was evaluated with five popular and available datasets. Three measurements; accuracy, time and ROC curve were considered to assess the efficiency. The experimental results show that the proposed approach can achieve a trade-off between time and accuracy by the multi-objective genetic algorithm. Moreover, using ensemble-classifiers approach, we increased the reliability of the model. Consequently, the proposed method promotes the detection accuracy in three of selected datasets in comparison of four recent suitable methods.

Optical fiber biosensor for measuring Packet Cell Volume concentration (PCV) of human blood depending on the attenuation of light is designed and implemented during this work. Its present a simple and accurate method to measure blood viscosity. Three lasers’ wavelengths have been used in this system. These lasers are He-Ne laser with (632nm) wavelength, (5 mw) power, laser diode with (532nm) wavelength, (20 mw) power and another laser diode with (430nm) wavelength, (20 mw) power. The system works by transmitting light through an optical fiber to the sample; the amount of light absorbed by the analyte is detected through a second fiber.

This paper came with the aim of knowing the causal mediation analysis and estimation methods in addition to the study data. Mediation is the basis for many fields, where at the present time the use of mediation analysis has become increasingly common in many areas of scientific research as well in other fields such as economic and social as well as medical sciences. Causal mediation analysis is one of the important methods in order to know the mechanism of influence between variables, which has had a large role among researchers in recent times. In order to arrive at a model that leads to accurate estimates, it is necessary to find or search for the method by which the important variables are chosen in order to be included in the model, especially when the study data suffers from the presence of the problem of linearity. Therefore, many methods of estimating the mediation variables have been used, which are the least squares method and Ridge method. In order to apply the estimation methods, a simple random sample of (50) women were drawn to study the factors affecting the number of births (response variable). The study data were analyzed using programming in R language.

This paper came with the aim of knowing the causal mediation analysis and estimation methods in addition to the study data. Mediation is the basis for many fields, where at the present time the use of mediation analysis has become increasingly common in many areas of scientific research as well in other fields such as economic and social as well as medical sciences. Causal mediation analysis is one of the important methods in order to know the mechanism of influence between variables, which has had a large role among researchers in recent times. In order to arrive at a model that leads to accurate estimates, it is necessary to find or search for the method by which the important variables are chosen in order to be included in the model, especially when the study data suffers from the presence of the problem of linearity. Therefore, many methods of estimating the mediation variables were used, which are the least squares method and the Lasso method. In order to apply the estimation methods, a simple random sample of (50) women were drawn to study the factors affecting the number of births (response variable). The study data were analyzed using programming in R language.

In the present work it has been investigated the repair of LP-blades steam turbine made of AISI 410 martensitic stainless steels (MSS) by GTAW welding, the repair welding carried out by using ER 310L as consumable filler wire. PWHT was carried out at 1100ᵒC for 1h. The structure-property relationships of the weldments were established based on the current modes employed by utilizing combined techniques of optical microscopy, line/point and EDS analysis. Results showed that Micro-hardness along the base and HAZ regions increased after PWHT as compared to in state of as-welded. After welding process, microstructure photographs of weld-metal region revealed two phase the vermicular δ-Ferrite and γ-austenite matrix. HAZ region consisted of tempered lath martensite with carbides. Line/Point analysis revealed the direction of segregation, whereas chromium was increased in core and depleted in boundary, while nickel was depleted in core and increased in boundary, this support the δ – ferrite was primarily solidified.