In this paper we present the theoretical foundation of forward error analysis of numerical algorithms under;• Approximations in "built-in" functions.• Rounding errors in arithmetic floating-point operations.• Perturbations of data.The error analysis is based on linearization method. The fundamental tools of the forward error analysis are system of linear absolute and relative a prior and a posteriori error equations and associated condition numbers constituting optimal of possible cumulative round – off errors. The condition numbers enable simple general, quantitative bounds definitions of numerical stability. The theoretical results have been applied a Gaussian elimination, and have proved to be very effective means of both a priori and a posteriori error analysis.
The strategy of designing the covers of international magazines emerges as one of the expressive means that reflect the emotional and expressive aspects and employ them according to the spatial transformations and the struggles of globalization to usurp the intellectual, cultural, value and civilizational essence of man, which makes him vulnerable to psychological and spiritual alienation and becomes the abstract meaning of identity and culture, and the empowerment of cultural invasion and the control of consumer thought The contemporary globalist on the largest area and the globalization of the peoples of the world, and the study came in the first chapter: the general framework that includes the problem of the research to raise in our m
... Show MoreReceipt date:11/19/2020 acceptance date:10/1/2021 Publishing date:12/31/2021
This work is licensed under a Creative Commons Attribution 4.0 International License.
Human rights are one of the basic concepts of modern and contemporary times, and political thought as the origin of political science and its source of knowledge have impact in this science and its branches
... Show MoreThis study produces an image of theoretical and experimental case of high loading stumbling condition for hip prosthesis. Model had been studied namely Charnley. This model was modeled with finite element method by using ANSYS software, the effect of changing the design parameters (head diameter, neck length, neck ratio, stem length) on Charnley design, for stumbling case as impact load where the load reach to (8.7* body weight) for impact duration of 0.005sec.An experimental rig had been constructed to test the hip model, this rig consist of a wood box with a smooth sliding shaft where a load of 1 pound is dropped from three heights.
The strain produced by this impact is measured by using rosette strain gauge connected to Wheatstone
Infrastructure projects, including buildings, bridges, and towers, in hilly or mountainous areas are frequently constructed on inclined landscapes. This work utilizes finite element limit analysis (FELA) to examine the effect of critical parameters on the ultimate bearing capacity (B.C.) of strip footings (S.F.) situated on slope faces. The analysis examines the impacts of Inclination of the Slope (β), Internal Friction Angle (ϕ), and embedment depth of footing (Df). As the slope angle (β) increased from 10° to 20°, the footing’s ultimate bearing capacity decreased by 55%. Furthermore, the embedded depth shows an important effect on the bearing capacity;
The governmental projects are considers the prevailing in Iraq, as most of the projects implemented by the Government, the major role played by governmental projects in the provision of services to citizens and improve the economic situation in the country in general, in addition to the huge number of these projects implemented by the governmental organizations and the large failure rates of it , and because of the fact that these projects are stumbled before they reach the stage of failure, The aim of this research to identify the main factors for the stumble projects in addition to identifying the most influential factor on the causes and consequences of it , like (cost overruns , time overruns , delay and scope
... Show MoreGiardia lamblia parasite was isolated from the diarrhea samples of patients with Giardiasis dysentery and was developed in HSP media, four mice groups have been used to find in vivo efficacy of two concentrations (128,256) mg/ml of chlorophorm extracts from Cladophora glomerata algae against Giardia lamblia parasite as compared with (Flagyl) by measuring several biochemical markers as ( GPT and GOT) enzymes ,sodium ,potassium and iron concentration as well as counting the number of parasitic cysts in each mice groups. The results demonstrate that levels of GPTA GOT enzymes have been decreased in mice treated with algal extract. As for the concentration of the Sodium, Potassium and Iron increased in mice treat
... Show MoreLeap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F
... Show MoreMost of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
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