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joe-2227
Optimized Zero and First Order Design of Micro Geodetic Networks
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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 applied to three cases of selected network to analyzed using the objective function of A-Optimality and D-Optimality, with selected range of movement of 300m to each point in each direction. The first case was a free network, the second case was with P55 and P73 as control points, and the third case was with P42 and P44 as control points. The results showed that the third case was the optimal design with high precision

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Publication Date
Sun Feb 22 2026
Journal Name
Pakistan Journal Of Pharmaceutical Sciences
Optimization And Development Of Ondansetron HCl Nanocrystals By Using D-Optimal Design Expert® And In-Vitro Characterization
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Background: Over the last few years, nanocrystal technology has expanded to improve the bioavailability of poorly water-soluble drugs, which is challenging. Nanocrystals (NCs) exhibit many properties, such as enhancing drug solubility, dissolution, oral absorption, and high drug loading. Ondansetron hydrochloride (ONH) is an antiemetic drug that antagonizes a serotonin 5-HT3 receptor in the peripheral and central nervous system and is widely prescribed for the management of chemotherapy and radiotherapy-induced vomiting and nausea, as well as for postoperative nausea. ONH exhibits approximately 60% bioavailability due to its poor solubility and first-pass metabolism in the liver. Its solubility is pH-dependent, its precipitates abov

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Publication Date
Thu Nov 15 2018
Journal Name
Journal Of Mathematical Imaging And Vision
A New Hybrid form of Krawtchouk and Tchebichef Polynomials: Design and Application
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Publication Date
Mon Dec 28 2020
Journal Name
Journal Of The College Of Education For Women
Evaluating the Indicators and Quality of Potable Water Networks in Al-Shatrah City: سميع جلاب منسي السهلاني
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The present paper aims at evaluating the vailability quality and future horizons of potable water in the city of Shatra as a model. This is done in accordance with certain subjective and objective factors alongside the classification map of Shatra as a residential area. This system follows geographical studies specialized in urban construction. The problem of the present paper as well as the data approaching that problem have been chosen from the records of 2018. The researcher offered (919) questionnaire forms to be answered by a sample of dwellers in that area. Besides, the researcher also followed lab analysis of water samples collected from districts in the city of Shatra. GIS technology was also used to arrive at the real water shar

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm for Improving the Quantity and Quality of the Detected Complexes from Protein Interaction Networks
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One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

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Publication Date
Mon Mar 27 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Design, Synthesis and Preliminary Antimicrobial Evaluation of New Derivatives of Cephalexin
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There is a continuous and massive need for newer cephalosporins that should have resistance against β-lactamases and can be used orally. An approach of using cephalexin, as a well-studied and potent antibacterial compound is considered to prepare new designed derivatives.  These derivatives include the incorporation of amino acid moiety linked through an amide bond with the α-amino group of cephalexin. Certain aliphatic amino acids were used, such as glycine, alanine, valine and proline. The chemical structures of these derivatives were confirmed by IR spectroscopy and elemental analyses. All the synthesized compounds were subjected for preliminary evaluation of antimicrobial activity using well diffusion method, against certa

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Publication Date
Thu Dec 01 2011
Journal Name
Swarm And Evolutionary Computation
Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks
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Publication Date
Tue Mar 25 2014
Journal Name
Sensors
Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects
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Publication Date
Thu Mar 24 2022
Journal Name
Arab World English Journal
Collocation Networks of Selected Words in Academic Writing: A Corpus-Based Study
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This study aims at shedding light on the linguistic significance of collocation networks in the academic writing context. Following Firth’s principle “You shall know a word by the company it keeps.” The study intends to examine three selected nodes (i.e. research, study, and paper) shared collocations in an academic context. This is achieved by using the corpus linguistic tool; GraphColl in #LancsBox software version 5 which was announced in June 2020 in analyzing selected nodes. The study focuses on academic writing of two corpora which were designed and collected especially to serve the purpose of the study. The corpora consist of a collection of abstracts extracted from two different academic journals that publish for writ

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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Science And Research (ijsr)
Height-to-Length Ratio Effect on the Response of Unreinforced Masonry Wall Subjected to Vertical Load Using Detailed-Micro Modeling Approach
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This paper aimed to investigate the effect of the height-to-length ratio of unreinforced masonry (URM) walls when loaded by a vertical load. The finite element (FE) method was implemented for modeling and analysis of URM wall. In this paper, ABAQUS, FE software with implicit solver was used to model and analysis URM walls subjected to a vertical load. In order to ensure the validity of Detailed Micro Model (DMM) in predicting the behavior of URM walls under vertical load, the results of the proposed model are compared with experimental results. Load-displacement relationship of the proposed numerical model is found of a good agreement with that of the published experimental results. Evidence shows that load-displacement curve obtained fro

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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