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Variants of Hybrid Genetic Algorithms for Optimizing Likelihood ARMA Model Function and Many of Problems
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Optimization is essentially the art, science and mathematics of choosing the best among a given set of finite or infinite alternatives. Though currently optimization is an interdisciplinary subject cutting through the boundaries of mathematics, economics, engineering, natural sciences, and many other fields of human Endeavour it had its root in antiquity. In modern day language the problem mathematically is as follows - Among all closed curves of a given length find the one that closes maximum area. This is called the Isoperimetric problem. This problem is now mentioned in a regular fashion in any course in the Calculus of Variations. However, most problems of antiquity came from geometry and since there were no general methods to solve such problems, each one of them was solved by very different approaches.

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Publication Date
Fri Dec 03 2021
Journal Name
2021 4th International Conference On Advanced Communication Technologies And Networking (commnet)
Methodology for Predicting the Optimum Design of Radio-Electronic Devices
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Development of an Integrated Construction Management System for Building Estimation
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Project management are still depending on manual exchange of information based on paper documents. Where design drawings drafting by computer-aided design (CAD), but the data needed by project management software can not be extracted directly from CAD, and must be manually entered by the user. The process of calculation and collection of information from drawings and enter in the project management software needs effort and time with the possibility of errors in the transfer and enter of information. This research presents an integrated computer system for building projects where the extraction and import quantities, through the interpretation of AutoCAD drawing with MS Access database of unit costs and productivities for the pricing and

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Publication Date
Sat Apr 03 2021
Journal Name
Lubricants
UV-Visible Spectrophotometer for Distinguishing Oxidation Time of Engine Oil
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Samples of gasoline engine oil (SAE 5W20) that had been exposed to various oxidation times were inspected with a UV-Visible (UV-Vis) spectrophotometer to select the best wavelengths and wavelength ranges for distinguishing oxidation times. Engine oil samples were subjected to different thermal oxidation periods of 0, 24, 48, 72, 96, 120, and 144 hours, resulting in a range of total base number (TBN) levels. Each wavelength (190.5 – 849.5 nm) and selected wavelength ranges were evaluated to determine the wavelength or wavelength ranges that could best distinguish among all oxidation times. The best wavelengths and wavelength ranges were analyzed with linear regression to determine the best wavelength or range to predict oxidation t

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Practical Study for the Properties of Hueckel Edge Detection Operator
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Publication Date
Tue Oct 30 2018
Journal Name
Risalat Al-huquq Journal
Legal Protection for Producers of Sound Recordings under Iraqi Law
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Piracy on phonograms is now, rightly, the crime of the electronic age. Despite the protection sought by States to provide for such registrations, whether at the level of national legislation or international agreements and conventions, but piracy has been and continues to pose a significant threat to the rights of the producers of those recordings, especially as it is a profitable way for hackers to get a lot of money in a way Illegal, which is contrary to the rules of legitimate competition. Hence, this research highlights the legal protection of producers of phonograms in light of the Iraqi Copyright Protection Act No. (3) of 1971, as amended.

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Publication Date
Sun Nov 01 2020
Journal Name
Travel Medicine And Infectious Disease
Incidence of the COVID-19 in Iraq – Implications for travellers
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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Engineering
Design of L1 -Adaptive Controller for Single Axis Positioning Table
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L1 adaptive controller has proven to provide fast adaptation with guaranteed transients in a large variety of systems. It is commonly used for controlling systems with uncertain time-varying unknown parameters. The effectiveness of  L1 adaptive controller for position control of single axis has been examined and compared with Model Reference Adaptive Controller (MRAC). The Linear servo motor is one of the main constituting elements of the x-y table which is mostly used in automation application. It is characterized by time-varying friction and disturbance.

    The tracking and steady state performances of both controllers have been assessed fo

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Surface Free Energy for the Evaluation of Asphalt Binder Stripping
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Stripping is one of the major distresses within asphalt concrete pavements caused due to penetration of water within the interface of asphalt-aggregate matrix. In this work, one grade of asphalt cement (40-50) was mixed with variable percentages of three types of additives (fly ash, fumed silica, and phosphogypsum) to obtained an modified asphalt cement to resist the effect of stripping phenomena .The specimens have been tested for physical properties according to AASHTO. The surface free energy has been measured by using two methods namely, the wilhelmy technique and the Sessile drop method according to NCHRP-104
procedures. Samples of asphalt concrete using different asphalt cement and modified asphalt cement percentages(4.1,4.6 an

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Publication Date
Sat Aug 01 2015
Journal Name
2015 37th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Tsallis entropy as a biomarker for detection of Alzheimer's disease
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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