The existing study aimed to assess four soil moisture sensors’ capacitive (WH51 and SKU: S EN0193) and resistive (Yl69 and IC Station) abilities, which are affordable and medium-priced for their accuracy in six common soil types in the central region of Iraq. The readings’ calibration for the soil moisture sensor devices continued through two gravimetric methods. The first depended on the protocols’ database, while the second was the traditional calibration method. The second method recorded the lowest analysis error compared with the first. The moderate-cost sensor WH51 showed the lowest standard error (SE), MAD , and RMSE and the highest R² in both methods. The performance accuracy of WH51 was close to readings shown by the manufac

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

Summary The objective of the research is to learn the design of a learning educational learning according to the theory of Ausubel in the acquisition of geographical concepts among the students of the fourth primary in the field of geography and the development of their habits of mind. To achieve this, the researcher relied on the two hypotheses the researcher used the design of equal groups the first experimental group was studied according to the design educational educational learning according to the theory and the other is an officer according to the traditional method. The research community consists of fourth grade pupils in primary school day for girls in the Directorate of Education Baghdad, Al-Rusafa, the third academic year 20

Background: This study was conducted to evaluate the surface roughness and dimensional accuracy of commercially obtainable alginate impression material in terms of imbibition after immersion in two different media. Materials and method: Two disinfecting agents, ethanol 70% and povidone-iodine 4%, were used to access the dimensional accuracy and surface roughness of alginate impression material. Weights of specimen discs of alginate impressions were measured before and immediately after immersion to gain a measure of imbibition. For surface roughness, disinfected specimens rectangle was examined before and after disinfection. Results: Minimal changes in weight were observed after disinfection, but a statistically non-significant differenc

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Background: Calcaneus is a spongy cancellous bone with rich blood supply , its fracture heals more rapidly providing no occurrence of infection and soft tissue injury around ,no gross malposition of fragments. The associated pain leads to a major impairment in life quality. The aim of treatment for calcaneal fractures is the decrease of pain and rebuilding of walking ability for patients with normal foot shape and the ability to wear normal foot wear. To reduce complications, a minimally invasive technique for the treatment of displaced intra-articular fractures of the calcaneus was preferred to use. The purpose of this study was to determine whether the closed reduction and percutaneous K. wire fixation of displaced intra-art

Background: Calcaneus is a spongy cancellous bone with rich blood supply , its fracture heals more rapidly providing no occurrence of infection and soft tissue injury around ,no gross malposition of fragments. The associated pain leads to a major impairment in life quality. The aim of treatment for calcaneal fractures is the decrease of pain and rebuilding of walking ability for patients with normal foot shape and the ability to wear normal foot wear. To reduce complications, a minimally invasive technique for the treatment of displaced intra-articular fractures of the calcaneus was preferred to use.

The purpose of this study was to determine whether the closed reduction and percutaneous K. wire fixation of displ

To investigate the efficacy of polyether‐ether‐ketone (PEEK) wire as a fixed orthodontic retainer, by comparing its performance to other retainer wires and optimizing its adhesion to composite bonding materials.

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,