Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

The research aims to identify the factors that affect the quality of the product by using the Failure Mode and Effect Analysis (FMEA) tool and to suggest measures to reduce the deviations or defects in the production process. I used the case study approach to reach its goals, and the air filter product line was chosen in the air filters factory of Al-Zawraa General Company. The research sample was due to the emergence of many defects of different impact and the continuing demand for the product. I collected data and information from the factory records for two years (2018-2019) and used a scheme Pareto Fishbone Diagram as well as an FMEA tool to analyze data and generate results.

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This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

The introduction of the research on the science of training and the physiology of sports was addressed from important sciences, where the physical effort drew the attention of scientists since the past centuries when they studied how the body performs its functions when performing physical exertion and observe the changes that occur in it and write down and study especially the positive effects of the practice of daily sports The aim of the study was to investigate the effect of plank exercises on the lipid component and the metabolic rate (bmr) of the female students of the Higher Institute for Security and Management Development. As for the third chapter, the two researchers used the experimental method on a sample of the female s

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

In addition to its basic communicative function, language can be used to imply information that is not actually stated, i.e. addressers do not always state exactly (or directly) what they mean. Such instances fall within the domain of pragmatics in that they have to do with how addressers use language to communicate in a particular situation by implication rather than by direct statement. The researcher attempts to demonstrate that the beauty and the multiple layers of meaning in poetry can be better explored if the addressee looks at the lines from a pragmatic perspective in search for implied meaning. There are many devices that can convey implied meaning in poetry, among which are 'rhetorical', 'figurative' or 'literary' devices. But

The current article focuses on studying the social organization reality of the Iraqi society; it aims to construct an Iraqi organized personality that believe in the principles of Islamic religion by making use of the sociology thoughts in explaining the strength of social organization, and the causes of social deviance in attempt of decreasing the deviance and strengthening the cohesion of Iraqi character.

The researchers put forward some questions: to what extent the western theoretical pattern can succeed in explaining the social organization of the Iraqi society? What is the more appropriate western theory for diagnosing the cohesion and deviance of the society? What is the s

Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti