This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr

Sewage water is a mixture of water and solids added to water for various uses, so it needs to be treated to meet local or global standards for environmentally friendly waste production. The present study aimed to analyze the new Maaymyrh sewage treatment plant's quality parameters statistically at Hilla city. The plant is designed to serve 500,000 populations, and it is operating on a biological treatment method (Activated Sludge Process) with an average wastewater inflow of 107,000m³/day. Wastewater data were collected daily by the Mayoralty of Hilla from November 2019 to June 2020 from the influent and effluent in the (STP) new in Maaymyrh for five water quality standards, such as (BOD5), (COD), (TSS), (TP)

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.

Electrocardiogram (ECG) is an important physiological signal for cardiac disease diagnosis. With the increasing use of modern electrocardiogram monitoring devices that generate vast amount of data requiring huge storage capacity. In order to decrease storage costs or make ECG signals suitable and ready for transmission through common communication channels, the ECG data
volume must be reduced. So an effective data compression method is required. This paper presents an efficient technique for the compression of ECG signals. In this technique, different transforms have been used to compress the ECG signals. At first, a 1-D ECG data was segmented and aligned to a 2-D data array, then 2-D mixed transform was implemented to compress the

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

The current research aims at recognize bullying for the pupils of the primary stage  and the students of the  middle stage  according to the gender variables and birth order also detection of difference significance of bullying among the variables of gender(males and females) and the birth order( the first, the second, the third, the forth, the fifth, and the sixth) and then detection of the bullying relation with these variables and to what extent each of them bullying degrees.

          To achieve this objective , the researcher has chosen a sample included(480) individual of(80) individual from the fourth grade primary school pupils and (100)

يهدف البحث الحالي التعرف على اسباب السرقة لدى تلاميذ المرحلة الابتدائية كما يراها معلموهم ومعلماتهم ، وعن الاساليب المتبعة في معالجة ظاهرة السرقة من قبلهم ، ولقد شملت عينة البحث على ( 200 ) فرداً من معلمي ومعلمات تلاميذ المرحلة الابتدائية في مدينة المكلا للعام الدراسي ( 2004 ـ 2005 ) ، وقد استخدمت الباحثة استبياناً أعدته كأداة للوصول الى اهداف البحث بعد ان تم التأكد من صدقه وثباته ، استخدمت الباحثة معادلة ارتب

This study aims to show, the strength of steel beam-concrete slab system without using shear connectors (known as a non-composite action), where the effect of the friction force between the concrete slab and the steel beam has been investigated, by using finite element simulation.

The proposed finite element model has been verified based on comparison with an experimental work. Then, the model was adopted to study the system strength with a different steel beam and concrete slab profile. ABAQUS has been adopted in the preparation of all numerical models for this study.

After validation of the numerical models, a parametric study was conducted, with linear and non-linear Regression analysis. An equation re

Awsaj (Lycium barbarum) is a plant belong to family Solanaceae serves as a good source of bioactive compounds like phytosterols which have many important biological activity. Literature survey available so far revealed that there was no studies about Iraqi wild Awsaj phytosterols especially B-sitosterol, there for the objective of this study was to examine the efficiency of ultrasound assisted extraction (probe and bath) as compared to the conventional (Soxhlet) extraction method for extraction of phytosterols especially B-sitosterol from fruits, leaves, stems and roots of Iraqi wild Awsaj plant. This goal was achieved by comparing the extraction mass yield, also by a quick and easy approach for identification and quantification of bioac