Market share is a major indication of business success. Understanding the impact of numerous economic factors on market share is critical to a company’s success. In this study, we examine the market shares of two manufacturers in a duopoly economy and present an optimal pricing approach for increasing a company’s market share. We create two numerical models based on ordinary differential equations to investigate market success. The first model takes into account quantity demand and investment in R&D, whereas the second model investigates a more realistic relationship between quantity demand and pricing.

This research attempted to take advantage of modern techniques in the study of the superstructural phonetic features of spoken text in language using phonetic programs to achieve more accurate and objective results, far from being limited to self-perception and personal judgment, which varies from person to person.
    It should be noted that these phonological features (Nabr, waqf, toning) are performance controls that determine the fate of the meaning of the word or sentence, but in the modern era has received little attention and attention, and that little attention to some of them came to study issues related to the composition or style Therefore, we recommend that more attention should be given to the study of

Diabetes imposes a substantial public health burden; according to the International Diabetes Federation, there were about 3.4 million diabetes related deaths worldwide in 2024, and in Iraq, the Federation reports that one in nine adults lives with diabetes in 2024, with 14,683 adult deaths attributable to diabetes and a total diabetes related health expenditure of 2,078 million United States dollars. The dataset analyzed in this study contains 1,000 records collected in 2020 from two Iraqi teaching hospitals and includes multiple clinical and laboratory measurements with three outcome classes, namely Non diabetic, Pre diabetic, and Diabetic, with a low prevalence of the Pre diabetic class and an imbalanced overall class distribution; the da

A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

AbstractBackground:Reduced glomeular filtration rate isassociated with increasedmorbidity in patientswith coronary arterydisease.Objectives :To analyze the declining eGFR andmortality risks in a patients with Chronic KidneyDisease and have had Coronary Artery Diseaseincluding risk factors .Patientsand Methods:The study included (160)patientsbetween the ages of 16 and 87years.Glomerular filtration rate was estimated (eGFR)using the Modification of Diet in Renal Diseaseequationand was categorized in the ranges<60 mL· min−1 per 1.73 m2and≥ 60 ml/min/1.73 m2.Baseline risk factors were analyzed by category ofeGFR,.The studied patients in emergencydepartment, were investigatedusing Coxproportional hazard models adjusting for traditiona

User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption user-face is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve