The aim of this paper is introducing the concept of (ɱ,ɳ) strong full stability B-Algebra-module related to an ideal. Some properties of (ɱ,ɳ)- strong full stability B-Algebra-module related to an ideal have been studied and another characterizations have been given. The relationship of (ɱ,ɳ) strong full stability B-Algebra-module related to an ideal that states, a B- -module Ӽ is (ɱ,ɳ)- strong full stability B-Algebra-module related to an ideal , if and only if for any two ɱ-element sub-sets and of Ӽɳ, if , for each j = 1, …, ɱ, i = 1,…, ɳ and implies Ạɳ( ) Ạɳ( have been proved..
This paper presents a method of designing and constructing a system capable of acquiring
the third dimension and reconstructs a 3D shape for an object from multi images of that object using
the principle of active optical triangulation. The system consists of an illumination source, a photo
detector, a movement mechanism and a PC, which is working as a controlling unit for the hard ware
components and as an image processing unit for the object multi view raw images which must be
processed to extract the third dimension. The result showed that the optical triangulation method
provides a rapid mean for obtaining accurate and quantitative distance measurements. The final
result's analysis refers to the necessity of usin
Abstract
Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance. This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H2/H∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS). Simulatio
... Show MoreThe main purpose of this work is the construction of an optical parametric amplifier (OPA) to generate a 629 nm pulsed laser. KTP nonlinear crystals were used for both parametric oscillation and amplification. A singly resonant parametric oscillator (OPO) is constructed to generate a signal of 1.54 μm and idler of 3.4 μm when the OPO system is pumped by 1.064 μm Q – switched Nd: YAG laser. The signal was then mixed with the pumping beam in OPA system to form the wanted wavelength. The obtained optical conversion efficiency was 60%.
This research was aimed to determine the petrophysical properties (porosity, permeability and fluid saturation) of a reservoir. Petrophysical properties of the Shuiaba Formation at Y field are determined from the interpretation of open hole log data of six wells. Depending on these properties, it is possible to divide the Shuiaba Formation which has thickness of a proximately 180-195m, into three lithological units: A is upper unit (thickness about 8 to 15 m) involving of moderately dolomitized limestones; B is a middle unit (thickness about 52 to 56 m) which is composed of dolomitic limestone, and C is lower unit ( >110 m thick) which consists of shale-rich and dolomitic limestones. The results showed that the average formation water
... Show MoreIn this paper, we introduce and discuss an extended subclass〖 Ą〗_p^*(λ,α,γ) of meromorphic multivalent functions involving Ruscheweyh derivative operator. Coefficients inequality, distortion theorems, closure theorem for this subclass are obtained.
Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c
... Show MoreThis study compared the clinicopathological, immunohistochemical characteristics and Epstein-Barr virus (EBV) detection of Burkitt's lymphoma (BL) in the abdomen and jaw of Iraqi patients. A cohort/retrospective study was carried out between August and September 2024 using 25 tissue blocks (14 gnathic and 11 abdominal BL) from the Oral and Maxillofacial Laboratory, University of Baghdad, College of Dentistry, and the National Centre for Educational Laboratories. The sections were stained with haematoxylin and eosin (H&E), while CD10, CD20, Bcl-2, BCl-6, C-Myc and Ki-67 markers were used for diagnosis. The DNA detection of the EBV was performed by polymerase chain reaction (PCR). The tumours showed 22 classical and 3 atypical histologi
... Show MoreThe purpose of this study is discuss the effect of Corporate Governance in the Tax Planning, has been made in a sample of Iraqi Industrial contribution Companies listed in Iraqi Stock Exchange Market (ISE) , for the period from 2008 to 2012.The study used the" Experimental Research Approach" . Also used the (Modified Jones Model, 1995) in order to measure the corporate governance, to measure the extent of the practice of corporate governance in the samples companies. While it use to measure tax planning, the model that used by studies and researches of tax that adopted in discussions of tax reform, by analyzing the financial statements of companies to reach a measurement for the two variables of the study. T
... Show MoreThis study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur
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