Our research is related to the projective line over the finite field, in this paper, the main purpose is to classify the sets of size K on the projective line PG (1,31), where K = 3,…,7 the number of inequivalent K-set with stabilizer group by using the GAP Program is computed.

In this paper thermo-hydrodynamic characteristics were investigated experimentally for a new type shell-helical coiled tube heat exchanger used as a storage tank of closed loop solar water heater system. Triple concentric helical coils were made of copper tubes of (12.5mm OD and 10mm ID) with coils diameter of (207, 152.2, 97mm) for outer, middle and inner coils respectively. The experiments were carried out during a clear sky days of (March and April 2012). The parameters studied in this work are: history of average temperature of shell side of the storage tank, collector heat gain, heat rejected from coils to shell side of the storage tank, collector efficiency, thermal effectiveness of the heat exchanger (storage tank), and pressure d

     Data mining is a data analysis process using software to find certain patterns or rules in a large amount of data, which is expected to provide knowledge to support decisions. However, missing value in data mining often leads to a loss of information. The purpose of this study is to improve the performance of data classification with missing values, ​​precisely and accurately. The test method is carried out using the Car Evaluation dataset from the UCI Machine Learning Repository. RStudio and RapidMiner tools were used for testing the algorithm. This study will result in a data analysis of the tested parameters to measure the performance of the algorithm. Using test variations: performance at C5.0, C4.5, and k-NN at 0% missi

This research sought to present a concept of cross-sectional data models,  A crucial double data to take the impact of the change in time and obtained from the measured phenomenon of repeated observations in different time periods, Where the models of the panel  data were defined by different types of fixed , random and mixed, and Comparing them by studying and analyzing the mathematical relationship between the influence of time with a set of basic variables Which are the main axes on which the research is based and is represented by the monthly revenue of the working individual and the profits it generates, which represents the variable response And its relationship to a set of explanatory variables represented by the

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

In the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assum

The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter  was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of  are derived from the relation between  and level density parameter . The formulae used to derive  are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on  from the Thomas-Fermi formula show a good agreement with the experimental data.

  To enlighten the extent of crude oil pollution effects on some anatomical characteristics of olive plant (Olea europaea ). Two years - old seedlings were chosen to grow under 5 levels of pollution (0.0, 0.5, 1.0, 2.0, and 3.0, liter/ plant). The experiment has been conducted in the experimental field of Natural History Research Center and Museum, University of Baghdad. It was designed as CRD experiment. Testing wood specimens were prepared after 2.5 years of growth. Fiber length, width, wall thickness, and wood specific gravity were measured. Results showed that olive plants could not resist the highest level ( 3 liters / plant ) of pollution .Fiber length was the most  affected property by treatment. All fiber dimensions wer