This research study examines the impact of information technology on firm profitability and stock returns. Using a comprehensive dataset of firms across various industries, this research employs rigorous statistical analysis techniques to investigate the relationship between IT investments, firm profitability metrics, and stock returns. The study focuses at how IT investments affect financial performance measures including return on assets (ROA) and return on equity (ROE), with P-values of 0.34 and 0.12, respectively. Furthermore, the study investigates the influence of IT on stock returns, taking into account market capitalization, industry trends, and macroeconomic variables. This study's conclusions center on the beneficial assoc

The increasing Global Competitive and the continuous improvement in information technology has led the way to the development of the modern systems and using modern techniques. One of these techniques is benchmarking style and Total Quality Management all of them are used to improve the production process and target rid from the losts on the other side.

The Benchmarking style has become a very important for all the industrial systems and the serving systems as well. And an instrument to improve their performance specially those which are suffering from the highness of the costs or waste in time on the other side.

This study aims to depend on virtual Benchmarking style in the eval

Background: Tear of MCL of the knee is a frequent problem among knee ligaments injuries.Injuries to the MCL are usually caused by contact on the outside of the knee and are accompanied by sharp pain on the inside of the knee. Contrary to most other knee ligaments the medial collateral ligament (MCL) has an excellent ability to heal, being fairly large and well vascularised structure. The vast majority of isolated medial ligament injuries heal without significant long-term problems

Objectives: is to compare between the early clinical examination, and assessment under general anesthesia (GA), and to find out the best methods to assess the MCL tear especially in suspected cases.

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ABSTRACT

            A laboratory experiment was carried out during winter season of 2021 in the Seed Technology Laboratory- College of Agricultural Engineering Sciences/ University of Baghdad, to find out the allopathic effects of aerobic and terrestrial aqueous extracts of Artemisia vulgaris L. on the seed germination and seedling growth of linseed. A factorial experiment according to a completely randomized design (CRD)at three replicates was used; the first factor in clouded type of aqueous extract for two plant parts which were aerobic (stems and leaves) and terrestrial (root and rhizomes), while the second factor included five concentrations

In this research we investigated the corrosion behavior of the commertialy pure titanium and Ti-6Al-4V alloy that coated with hydroxyapatite by electrochemical deposition with applied voltage (6,9,12) Volt from aqueous solution containing Ca(NO3)2.H2O =7.0 gm/l , (NH4)2HPO4 =3.5 gm/l , Na(NO3)2 = 8.5 gm/l in order to improve the bonding strength of hydroxyapetite and medical metals and alloys and increasing the biocompatibility. The coating layer morphology was investigated by XRD, Optical microscope , and SEM tests, the corrosio tests was made by use senthesys simulated body fluid (SBF) , and we found that the propreate voltage for coatint on Ti was 9 Volt and for Ti-6Al-4Vwas12Volt.

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

Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.

The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and