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Journal JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences

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JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 406-419; doi:10.29196/jubpas.v27i3.2554

Abstract:The complexes of Co(II), Cu(II) and Ni(II) were synthesized by using schiff base – azo as a ligand, which were prepared under this study by the reaction between the Schiff base diazonium salt and the imidazole derevitive. They were characterized by element analysis, FTIR spectroscopy and UV.VIS. spectroscopy. Their electric conductivity and magnetic features were determined. Their stepwise and overall stability constants and their thermodynamic data ( , and ) were determined. The results showed that all the complexes have paramagnetic features and all of them have good conductivity. The formula of the complexes under this paper were suggested by using the mole ratio method which lead to the formation of (1 : 2) metal : ligand formula for all the complexes. In all the complexes the coordinated sites was through N atoms of the azo groups and N atom of the imidazol ring. The suggested geometrical shapes of the complexes was the octahedral shape due to the ( d2sp3 ) hybridization. Their stepwise stability constants were determined, it was found that for all the complexes they were increased toward the addition of ligand that because of the chelate effect. Their overall stability constants were determined, it was found that for all the complexes were high that because of the chelate effect. Their thermodynamic functions ( , and ) were had negative value, that refer to good stability for the complexes and these results were satisfied with the spontaneous reaction and high stability complexes.
Taiwo Abass Ishola, Olatayo Timothy Olabisi, Adesanya Kazeem Kehinde
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 519-526; doi:10.29196/jubpas.v27i1.2208

Abstract:Trigonometric Polynomial Regression is a form of non-linear regression in which the relationship between the outcome variable and risk variable is Fractional modeled as 1/nth degree polynomial regression by combining the function of cos(nx) and sin(nx) on the value of natural numbers. The model was used to analyze the relationship between three continuous and periodic variables. Coefficients of the model were estimated using the Maximum Likelihood Estimate (MLE) method. From the results, the model obtained indicated that an increased in body mass index will increase the level of blood pressure while age may or may not have an influence on the blood pressure level. The values of the Coefficient of variation showed the variation in the dependent variable was well explained by the independent variables and the value of the adjusted coefficient of determination showed the model had a good fit with a high level of predictive power.
Sciprofile linkHussein Altabrawee, Osama Abdul Jaleel Ali, Sciprofile linkSamir Qaisar Ajmi
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 194-205; doi:10.29196/jubpas.v27i1.2108

Abstract:The ultimate goal of any educational institution is offering the best educational experience and knowledge to the students. Identifying the students who need extra support and taking the appropriate actions to enhance their performance plays an important role in achieving that goal. In this research, four machine learning techniques have been used to build a classifier that can predict the performance of the students in a computer science subject that is offered by Al-Muthanna University (MU), College Of Humanities. The machine learning techniques include Artificial Neural Network, Naïve Bayes, Decision Tree, and Logistic Regression. This research pays extra attention to the effect of using the internet as a learning resource and the effect of the time spent by students on social networks on the students’ performance. These effects introduced by using features that measure whether the student uses the internet for learning and the time spent on the social networks by the students. The models have been compared using the ROC index performance measure and the classification accuracy. In addition, different measures have been computed such as the classification error, precision, recall, and the F measure. The dataset used to build the models is collected based on a survey given to the students and the students’ grade book. The ANN (fully connected feed forward multilayer ANN) model achieved the best performance that is equal to 0.807 and achieved the best classification accuracy that is equal to 77.04%. In addition, the decision tree model identified five factors as important factors which influence the performance of the students.
Mufeed Thinun Younis, Dina Ahmed Omer
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 358-366; doi:10.29196/jubpas.v27i2.2266

Abstract:The research aims to study the inter-relationship between global competitiveness indicators and human development indicators for selected countries (low, middle, and high income)by using Granger Test, and VAR Test. The results of the causality test showed that there is a causality relation between international competitiveness and human development. We found global competitiveness indicators has a clear effect on human development indicators in the low, middle, and high-income countries.
Ali Hakem Jabor, Ali Hussein Ali
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 171-183; doi:10.29196/jubpas.v27i1.2106

Abstract:The features selection is one of the data mining tools that used to select the most important features of a given dataset. It contributes to save time and memory during the handling a given dataset. According to these principles, we have proposed features selection method based on mixing two metaheuristic algorithms Binary Particle Swarm Optimization and Genetic Algorithm work individually. The K-Nearest Neighbour (K-NN) is used as an objective function to evaluate the proposed features selection algorithm. The Dual Heuristic Feature Selection based on Genetic Algorithm and Binary Particle Swarm Optimization (DHFS) test, and compared with 26 well-known datasets of UCI machine learning. The numeric experiments result imply that the DHFS better performance compared with full features and that selected by the mentioned algorithms (Genetic Algorithm and Binary Particle Swarm Optimization).
Rafid K Nsaif Al-Obaidi, Hud Dhim J. Ka Al-Hailly
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 249-276; doi:10.29196/jubpas.v27i1.2120

Abstract:The most of the production plants in Iraq apply traditional cost systems, which depend on the distribution of the total costs on the basis of which may be unconsidered, leading to the loading of the final product at unhelpful costs, whether directly or indirectly, so the system of cost-accounting based on activities (ABC) to help the unit in the evaluation and regulation of costs through the study and analysis of the activities and costs realized for those activities this study showed through the theoretical and applied study on the reality of the General Company for Textile Industries in Hilla. that the cost system applied in the company is traditional and thus load the cost is not limited by the need to develop precise cost engines by specialists with accounting and cost experience, especially with the diversity and abundance of products. The basis of one load rate is used at the level of the company as a whole, namely the productive unit, ie the total indirect industrial costs of the centers Marketing and management services) after direct exclusion whether variable or fixed as easy to track. The most important findings of the study are that the method of ABC is more accurate in measuring and determining the cost of production and the cost of a meter than the traditional method. This is reflected in the control, planning and decision making. This method provides more accurate and objective data for management. The most important recommendation of the study is to apply the cost-based system (ABC) because it leads to accuracy and objectivity in cost measurement, analysis of activities, selection of causes for accurate costs and measurement of outputs in the reports to make sound management decisions.
Mohanad O. Abdullah Al-Jubouri, Abdul-Razak M. Mohamed
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 306-316; doi:10.29196/jubpas.v27i2.2223

Abstract:Some biological characteristics of shabbot, Arabibarbus grypus (Heckel, 1843) in the Al-Diwaniya River, middle of Iraq were studied from October 2016 to September 2017. Water temperature ranged from 10.2oC in March to 32.8oC in August. A total of 853 fish were caught by seine, gill and cast nets and electro-fishing. A. grypus constituted about 6.27% of the total fish catch. The length-weight relationship was W=0.021*L2.7548 revealing an allometric growth. The mean relative condition factor was 0.91. Five age groups wore recorded and their mean total lengths were 20.2, 32.0, 39.0, 43.9 and 48.4 cm, respectively. The growth model of the species was Lt= 58 [1-e -0.39 (t-0.313)]. The growth performance index (Φ) of A. grypus was computed as 3.11. The study declares that the species is a omnivore, feeding mainly on aquatic plants, insects, algae and detritus. The overall sex ratio (female: male) was 1.47:1. The highest values of gonado- somatic index (GSI) were 4.20 for female and 1.78 for males in April. The fecundity of the species ranged from 75600 to 124200 eggs.
Salwa Salman Abed, Anaam Neamah Faraj
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 329-340; doi:10.29196/jubpas.v27i2.2228

Abstract:In this paper, we introduce the Hutchinson Barnsley operator (shortly, operator) on a metric space and employ its theory to construct a fractal set as its unique fixed point by using Ciric type generalized -contraction in complete metric space. Some concepts are illustrated by numerical examples.
Sciprofile linkNihal A. Abdulwahhab, Ferruccio Renzoni
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 457-467; doi:10.29196/jubpas.v27i1.2219

Abstract:The Bose-Einstein condensate (BEC) is created in a magnetic trap in the Quadrupole-Ioffe configuration (QUIC). This kind of trap combines an anti-Helmholtz quadrupole field with an offset field produced by a single coil perpendicular to the quadrupole field axis to suppress Majorana transitions. In the quadrupole trap evaporative cooling is performed by using radio frequency, reaching the phase transition to a BEC in the QUIC trap. By using Time of Flight (TOF) technique, the expansion velocity is measured with and which lead to temperature of and It is roughly around the recoil temperature.
JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, Volume 27, pp 356-367; doi:10.29196/jubpas.v27i1.2191

Abstract:The student’s retention rate is one of the challenging issues that representing the quality of the university. A high dropout rate of students affects not only the reputation of the university but also the students’ career in the future. Therefore, there is a need of student dropout analysis in order to improve the academic plan and management to reduce students drop out from the university as well as to enhance the quality of the higher education system. Data mining technique provides powerful methods for analysis and the prediction the dropout. This paper proposes a model for predicting students’ dropout using the dataset from the representative of the largest public university in the Southen part of Thailand. In this study, data from Faculty of Science, Prince of Songkla University was collected from academic year of 2013 to 2017. The experiment result shows that JRip rule induction is the best technique to generate a prediction model receiving the highest accuracy value of 77.30%. The results highlight the potential prediction model that can be used to detect the early state of dropping out of the student which the university can provide supporting program to improve the student retention rate
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