This study aims to determine the relationship between psychological frequency and the accuracy of receiving a serve in volleyball. The researchers used a descriptive approach, which is best suited to the research problem. The study sample consisted of 12 players from the University of Baghdad volleyball team. Ten players were selected purposively, and two were excluded from the research sample for use in a pilot study, as well as players who participate in volleyball at sports clubs. The sample size represented 83% of the original population. The researchers used the Psychological Frequency Scale developed by Firas Abdul Hussein (1999) for sports-related applications, which consists of 51 positive and negative items. The SPSS version 26 sof

Background: Menstrual problems with all manifestations ranging from life-threatening bleeding to amen- orrhea are considered patterns of abnormal uterine bleeding (AUB), which is until now a popular reason for referral to the gynaecologic clinic and requires a special diagnostic tool. Objective: To assess the accuracy of hysteroscopy in diagnosing endometrial pathologies and to compare it with sonographic and histopathologic reports. Patients and Methods: A prospective study conducted in the Baghdad Teaching Hospital on 60 Iraqi females having varying complaints from abnormal uterine bleeding in pre- and post-menopausal women, infertility, and chronic pelvic pain with normal or abnormal ultrasound findings. Office hysteroscopy was done and

The research aims Modifying the accuracy test for the diagonal and straight high smash skill from center (4) according to the body position of the Premier League volleyball players and extracting the grades and standard levels. To achieve the two objectives of the research: the descriptive approach with the survey method was adopted, because it agrees in solving the research problem. As for the research sample, it consisted Of the players in the Premier League for volleyball clubs for the 2023-2024 season, the researcher chose central players (4)(2) because their skill abilities are compatible with the skill of hitting the diagonal and straight smashes, and they numbered (90) players (6 players from each team), and then the researche

Building Information Modeling (BIM) and Lean Construction (LC) are two quickly growing applied research areas in construction management. This study focuses on identifying the most essential benefits and analyzing the most affecting constraints on the construction sector that construction players face as they attempt to combine BIM-LC in Iraqi construction. Experts assessed 30 benefits and 28 constraints from examining the previous literature, and a two-round Delphi survey formed the responses. Expert consensus analysis was utilized to elaborate and validate responses after descriptive statistical checks had been used for data processing.

According to the study's findings, the benefits include ensuring the most ef

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

<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

Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs