In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

KE Sharquie, AA Noaimi, AS Alaboudi, Journal of Cosmetics, Dermatological Sciences and Applications, 2012 - Cited by 3

Background: Coronary artery disease (CAD) is one of the leading causes of death worldwide. Clopidogrel, antiplatelet drug, has been widely used for management of CAD. Arylesterase, the activity of Paraoxonase-1 (PON-1), is mainly contributed in the biotransformation of clopidogrel to its active thiol form. The purpose of this study was to investigate the effect of receiving clopidogrel drug on the arylesterase activities in CAD patients. The effect of receiving clopidogrel drug on the antioxidant activity of arylesterase was also monitored by determination of malondialdehyde (MDA) level. Methods: One hundred CAD patients, who were followed-up for 5 days after reciving clopidogrel, and 50 healthy volunteers were included in our study

In recent years, the Global Navigation Satellite Services (GNSS) technology has been frequently employed for monitoring the Earth crust deformation and movement. Such applications necessitate high positional accuracy that can be achieved through processing GPS/GNSS data with scientific software such as BERENSE, GAMIT, and GIPSY-OSIS. Nevertheless, these scientific softwares are sophisticated and have not been published as free open source software. Therefore, this study has been conducted to evaluate an alternative solution, GNSS online processing services, which may obtain this privilege freely. In this study, eight years of GNSS raw data for TEHN station, which located in Iran, have been downloaded from UNAVCO website

Obesity and cancer are two major epidemics of this century. Obesity is related to a higher risk of many types of cancer. Studies have accessed circulating adipokines, as key-mediators in obesity and breast cancer. The study is aimed to examine the circulating levels of insulin-like growth factor-1, leptin, adiponectin, and resistin in premenopausal Iraqi women with breast cancer. The current study was performed during the period from June 2019 to December 2019 at Oncology unit/ Medical City Hospital-Baghdad. A total of 90 premenopausal women with BC/ stage II and III after 2nd dose of chemotherapy were contributed in this study as patients group. Their ages ranged from (35- 50) years in addition to 90 premenopausal healthy women wer

Background:    Hip fractures are common, morbid, and costly health events that threaten independence and function of older patients . Early functional recovery is extremely important for elderly patients with femoral intertrochanteric fractures to shorten their hospital stay, omit the necessity of the further nursing and care services, and reduce associated medical expenditures . Assessment of  (ADL) is an important predictor of outcomes Of orthopedic surgery in very early postoperative period at two weeks and a month postoperatively using Japanese orthopedic score get a quick recovery of ADL & return the patient to his or her premorbid level function reducing the morbidity and mortality.

Although rare, coarctation of aorta is a treatable cause of hypertension, transcatheter dilatation by balloon with or without stent are a well-known treatment strategy

Feed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 m