Background: Osteoarthritis OA is the most common joint disorder in the world. Injection of high molecular weight hyaluronic acid intra-articular with steroid is a one of the used therapeutic option for patients with (OA)knee.

Objectives: Objective of this study was the evaluation the efficacy, safety, pluse duration of action of viscosupplementation of the  HMWHA( high molecular weight hyluranic acid ).

Type of the study: Cross-sectional study.

Methods: From 81 patients with sever knee pain due to OA (grades 3–4) were recruited from Al-Yarmouk teaching hospital  & a private clinic during the period from January 2014 till July 2016.

Background/Aim: Knee osteoarthritis is a frequently crippling chronic condition. Numerous pharmacological medications have been successfully utilised to treat knee osteoarthritis. This research aimed to compare the efficiency of metformin and serratiopeptidase in treating and preventing osteoarthritis development via distinct mechanisms. Methods: Between 1 January and 30 May 2019, a randomised-clinical-trial was done at Al-Kindy Hospital on 80 osteoarthritis patients, divided in two groups. Group I was given metformin 850 mg orally, whereas Group II was given serratiopeptidase 20 mg and metformin 850 mg orally. Parameters in these groups were compared with forty healthy normal controls. Results: Following treatment, patients in Grou

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,

Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

تم استخدام خرائط ضبط الجودة الإحصائية لتقييم جودة الخدمة التعليمية في جامعة الباحة،  ويهدف هذا البحث إلى استخدام خرائط ضبط الجودة الإحصائية لقياس مستوى الجودة وفجوة الجودة بين توقعات الطلبة وإدراكاتهم لمستوى الخدمة الذي تقدمه جامعة الباحة. حيث تم اختيار عينة من 200 طالب وطالبة عشوائيا باستخدام العشوائية العنقودية من 4 كليات خلال الفترة 01 – 30/2015م، وجمعت البيانات من خلال استبيان جودة الخدمة الذي يقيس ت

Precision is one of the main elements that control the quality of a geodetic network, which defines as the measure of the network efficiency in propagation of random errors. This research aims to solve ZOD and FOD problems for a geodetic network using Rosenbrock Method to optimize the geodetic networks by using MATLAB programming language, to find the optimal design of geodetic network with high precision. ZOD problem was applied to a case study network consists of 19 points and 58 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P55 and P73 having the minimum ellipse of error and considered as control points. FOD problem was applie

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback