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 the trend of the stock if it is a rising stock or a descending stock .The aim of the research is to classify the financial stock data using five variables where the data of the Iraqi Islamic Bank for investment and development was used where the results showed the accuracy of the algorithm, the support vector machine and the CART algorithm, and their performance was good. Also, the results showed that the Support Vector Machines algorithm is the best when compared with the CART algorithm, using the Classification Error and MSE criteria
Due to the developments taking place in the field of communications, informatics systems and knowledge management in the current century, and the obligations and burdens imposed on the business organization to keep pace with these developments, the traditional methods of administrative decision-making are no longer feasible, as recent trends have emerged in management that focus on the need to rely on quantitative methods such as operations research.. The latter is one of the results of World War II, which appeared for the first time in Britain to manage war operations. The first method used in this field is the linear programming method. The use of operations research has developed greatly in the past years, and the methods of analysis in
... Show MoreImage processing applications are currently spreading rapidly in industrial agriculture. The process of sorting agricultural fruits according to their color comes first among many studies conducted in industrial agriculture. Therefore, it is necessary to conduct a study by developing an agricultural crop separator with a low economic cost, however automatically works to increase the effectiveness and efficiency in sorting agricultural crops. In this study, colored pepper fruits were sorted using a Pixy2 camera on the basis of algorithm image analysis, and by using a TCS3200 color sensor on the basis of analyzing the outer surface of the pepper fruits, thus This separation process is done by specifying the pepper according to the color of it
... Show Moreيرغب المرء أن يعيش في منزل يعبر عن اصالة تصميمه ذا اهداف جمالية كحاجته الى تحقيق الأهداف العملية. وعليه فمن الأهمية بمكان ان يشارك أصحابه مع المعنيين[1] بشؤون التصميم... وهنا ارتأت الباحثة ان تقوم بدراسة علمية حديثة حول ورق الجدران ثلاثي الابعاد وتوظيفة في غرفة المعيشة, وباسلوب عصري حديث يجمع بين جمالية التصميم والحداثة , إضافة الى تناول الإضاءة لما لها من دور في ابراز معالم وتفاصيل الأثاث
... Show MoreThe novels that we have addressed in the research, Including those with the ideological and political ideology, It's carry a negative image for the Kurds without any attempt to understand, empathy and the separation between politics and the people, The novels were deformation of the image, Like tongue of the former authority which speaks their ideas, Such as (Freedom heads bagged, Happy sorrows Tuesdays for Jassim Alrassif, and Under the dogs skies for Salah Salah). The rest of novels (Life is a moment for Salam Ibrahim, The country night for Jassim Halawi, The rib for Hameed Aleqabi). These are novels contained a scene carries a negative image among many other social images, some positive, and can be described as neutral novels. We can
... Show MoreIn this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.
A new way to Systems concentrates have been clarified and that allows a concentration high and analysis to automatically wavelengths of the spectrum of this system analyst of the spectrum and the center is built on Holucram Nafez gives less absorbency with efficient diffraction high when the wavelength (900 nm), which will be useful for Khallaya solar
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
... Show MoreBackground: Mother-infant bonding is an important psychological step postpartum and disturbed relationship may carry dramatic consequences as a psychological disorder which may affect the periodontal health of the mother. The aim of the present study was to assess the effect of the postpartum Mother-infant bonding on their periodontal condition. Materials and Methods: Mothers in the postpartum period with age range 20-35 years were subjected to postpartum Bonding Questionnaire (PBQ). Periodontal health status was assessed by measuring probing pocket depth and clinical attachment level. Results: The mean values of both probing pocket depth (PPD) and clinical attachment loss (CAL) were higher among disordered mothers than mothers with normal
... Show More<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c
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