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Multiobjective Optimization of Stereolithography for Dental Bridge Based on a Simple Shape Model Using Taguchi and Response Surface Methods
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Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi method with response surface methodology and the desirability function technique. The predicted optimal values for the cube’s dimensional deviation and surface roughness were 0.0517 mm and 2.8079 µm, respectively. The experiments’ validation of the findings confirmed the results, which were determined to be 0.0560 and 0.064667 mm and 2.770 and 2.6431 µm for the dimensional deviation and surface roughness for the cube and bridge, respectively. The percentages of prediction errors between the predicted optimum results and the printed response were 7.68% and 1.36% for dimensional deviation and surface roughness, respectively. This study demonstrates that the robust method used produced a dental bridge with good accuracy and a smooth surface.

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Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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Publication Date
Thu Oct 01 2015
Journal Name
International Journal Of Engineering And Advanced Technology (ijeat)
Optimization Process Parameters of Submerged Arc Welding Using Taguchi Method
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Submerged arc welding (SAW) process is an essential metal joining processes in industry. The quality of weld is a very important working aspect for the manufacturing and construction industries, the challenges are made optimal process environment. Design of experimental using Taguchi method (L9 orthogonal array (OA)) considering three SAW parameter are (welding current, arc voltage and welding speed) and three levels (300-350-400 Amp. , 32-36-40 V and 26-28-30 cm/min). The study was done on SAW process parameters on the mechanical properties of steel type comply with (ASTM A516 grade 70). Signal to Noise ratio (S/N) was computed to calculate the optimal process parameters. Percentage contributions of each parameter are validated by using an

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Publication Date
Thu Dec 19 2024
Journal Name
Iraqi Journal Of Mechanical And Material Engineering
STUDY ON THE PARAMETER OPTIMIZATION INMAGNETIC ABRASIVE POLISHING FORBRASS CUZN33PLATE USING TAGUCHI METHOD
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This paper describes a new finishing process using magnetic abrasives were newly made to finish effectively brass plate that is very difficult to be polished by the conventional machining processes. Taguchi experimental design method was adopted for evaluating the effect of the process parameters on the improvement of the surface roughness and hardness by the magnetic abrasive polishing. The process parameters are: the applied current to the inductor, the working gap between the workpiece and the inductor, the rotational speed and the volume of powder. The analysis of variance(ANOVA) was analyzed using statistical software to identify the optimal conditions for better surface roughness and hardness. Regressions models based on statistical m

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Surface Shape Descriptors on 3D Faces
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The general objective of surface shape descriptors techniques is to categorize several surface shapes from collection data. Gaussian (K) and Mean (H) curvatures are the most broadly utilized indicators for surface shape characterization in collection image analysis. This paper explains the details of some descriptions (K and H), The discriminating power of 3D descriptors taken away from 3D surfaces (faces) is analyzed and present the experiment results of applying these descriptions on 3D face (with polygon mesh and point cloud representations). The results shows that Gaussian and Mean curvatures are important to discover unique points on the 3d surface (face) and the experiment result shows that these curvatures are very useful for some

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Publication Date
Thu Feb 25 2021
Journal Name
Iraqi Journal Of Agricultural Sciences
OPTIMIZATION OF LEVOFLOXACIN REMOVAL FROM AQUEOUS SOLUTION USING ELECTROCOAGULATION PROCESS BY RESPONSE SURFACE METHODOLOGY
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This study was aimed to investigate the response surface methodology (RSM) to evaluate the effects of various experimental conditions on the removal of levofloxacin (LVX) from the aqueous solution by means of electrocoagulation (EC) technique with stainless steel electrodes. The EC process was achieved successfully with the efficiency of LVX removal of 90%. The results obtained from the regression analysis, showed that the data of experiential are better fitted to the polynomial model of second-order with the predicted correlation coefficient (pred. R2) of 0.723, adjusted correlation coefficient (Adj. R2) of 0.907 and correlation coefficient values (R2) of 0.952. This shows that the predicted models and experimental values are in go

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
A Genetic Based Optimization Model for Extractive Multi-Document Text Summarization
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Extractive multi-document text summarization – a summarization with the aim of removing redundant information in a document collection while preserving its salient sentences – has recently enjoyed a large interest in proposing automatic models. This paper proposes an extractive multi-document text summarization model based on genetic algorithm (GA). First, the problem is modeled as a discrete optimization problem and a specific fitness function is designed to effectively cope with the proposed model. Then, a binary-encoded representation together with a heuristic mutation and a local repair operators are proposed to characterize the adopted GA. Experiments are applied to ten topics from Document Understanding Conference DUC2002 datas

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Publication Date
Thu Oct 01 2020
Journal Name
Alexandria Engineering Journal
Biodegradation of reactive dyes by some bacteria using response surface methodology as an optimization technique
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Water pollution as a result of contamination with dye-contaminating effluents is a severe issue for water reservoirs, which instigated the study of biodegradation of Reactive Red 195 and Reactive Blue dyes by E. coli and Bacillus sp. The effects of occupation time, solution pH, initial dyes concentrations, biomass loading, and temperature were investigated via batch-system experiments by using the Design of Experiment (DOE) for 2 levels and 5 factors response surface methodology (RSM). The operational conditions used for these factors were optimized using quadratic techniques by reducing the number of experiments. The results revealed that the two types of bacteria had a powerful effect on biodegradable dyes. The regression analysis reveale

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Publication Date
Tue Mar 26 2019
Journal Name
Iraqi Journal Of Science
Classical and Statistical Optimization by Response Surface Methodology For Enhancing Biomass and Bacteriocin Production by Lactobacillus Plantarum
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Response surface methodology (RSM) based on central composite design was successfully applied to redesign MRS media for maximizing both biomass and bacteriocin production from Lactobacillus plantarum NH40. First, glucose and yeast extract were chosen as the best carbon and nitrogen sources based on classical optimization results of one factor at time which also revealed the possibility of eliminating peptone and meat extract from the original composition of medium without affecting the growth and bacteriocin production. Statistical experimental design based on a regression model generated using the Design expert 7 software showed that the optimum concentrations of glucose, yeast extract, tween80, NH4Cr, CH

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Optimization of Fenton process for removal of chemical oxygen demand (COD) from hospital wastewater using response surface methodology (RSM)
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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Surface Roughness and Material Removal Rate in Electrochemical Machining Using Taguchi Method
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Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

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