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Multi-Objective Shortest Path Model for Optimal Route between Commercial Cities on America
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The traditional shortest path problem is mainly concerned with identifying the associated paths in the transportation network that represent the shortest distance between the source and the destination in the transportation network by finding either cost or distance. As for the problem of research under study it is to find the shortest optimal path of multi-objective (cost, distance and time) at the same time has been clarified through the application of a proposed practical model of the problem of multi-objective shortest path to solve the problem of the most important 25 commercial US cities by travel in the car or plane. The proposed model was also solved using the lexicographic method through package program Win-QSB 2.0 for operational research applications.

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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Fri Aug 28 2020
Journal Name
Iraqi Journal Of Science
An application of Barnacle Mating Optimizer in Infectious Disease Prediction: A Dengue Outbreak Cases
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Meta-heuristic algorithms have been significantly applied in addressing various real-world prediction problem, including in disease prediction. Having a reliable disease prediction model benefits many parties in providing proper preparation for prevention purposes. Hence, the number of cases can be reduced. In this study, a relatively new meta-heuristic algorithm namely Barnacle Mating Optimizer (BMO) is proposed for short term dengue outbreak prediction. The BMO prediction model is realized over real dengue cases data recorded in weekly frequency from Malaysia. In addition, meteorological data sets were also been employed as input. For evaluation purposes, error analysis relative to Mean Absolute Percentage Error (MAPE), Mean Square Err

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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
Construction Time-Cost Optimization Modeling Using Ant Colony Optimization
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In the field of construction project management, time and cost are the most important factors to be considered in planning every project, and their relationship is complex. The total cost for each project is the sum of the direct and indirect cost. Direct cost commonly represents labor, materials, equipment, etc.
Indirect cost generally represents overhead cost such as supervision, administration, consultants, and interests. Direct cost grows at an increasing rate as the project time is reduced from its original planned time. However, indirect cost continues for the life of the project and any reduction in project time means a reduction in indirect cost. Therefore, there is a trade-off between the time and cost for completing construc

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Publication Date
Mon Sep 20 2021
Journal Name
Key Engineering Materials
Effect of Partial Substitution of Sr by Ba on the Structural Properties of Tl<sub>0.8</sub>Ni<sub>0.2</sub>Sr<sub>2-x</sub>Br<sub>x</sub>Ca<sub>2</sub>Cu<sub>3</sub>O<sub>9-δ</sub> System
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In this manuscript, the effect of substituting strontium with barium on the structural properties of Tl0.8Ni0.2Sr2-xBrxCa2Cu3O9-δcompound with x= 0, 0.2, 0.4, have been studied. Samples were prepared using solid state reaction technique, suitable oxides alternatives of Pb2O3, CaO, BaO and CuO with 99.99% purity as raw materials and then mixed. They were prepared in the form of discs with a diameter of 1.5 cm and a thickness of (0.2-0.3) cm under pressures 7 tons / cm2, and the samples were sintered at a constant temperature o

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Extraction ،Purification and Characterization Of Peroxidase From cabbage (Brassica oleracea Var)
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The activity of peroxidase (POD) in cabbage was evaluated using
spectrophotometric method. The enzyme was extracted from the cabbage leaves
with 0.1 M phosphate buffer solution pH 7. 0 . POD activity was determined using
(O-dianisidine) as a substrate. The effects of the amounts of enzyme extract,
substrate concentration, pH and temperature were investigated. The highest activity
of POD was recored at 2 mg/ml. The highest activity of POD was optimized with
16 mM O-dianisidine, The optimum pH was 7.0 for POD , The optimum
temperature was 30°C for POD. These optimum conditions were used to
determined the enzyme activities in cabbage sample. Acetone fractionated
peroxidase from crude extract of Brassica oleracea

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Taxonomy of Memory Usage in Swarm Intelligence-Based Metaheuristics
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Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
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 applie

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Image Compression Using 3-D Two-Level Technique
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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r

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Publication Date
Thu Jan 30 2025
Journal Name
Journal Of Engineering
Image Compression Using 3-D Two-Level Techniques
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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
طرائق جديدة لحل مشاكل البرمجة الخطية الضبابية المتماثلة
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Several authors have used ranking function for solving linear programming problem. In This paper is proposed two ranking function for solving fuzzy linear programming and compare these two approach with trapezoidal fuzzy number .The proposed approach is very easy to understand and it can applicable, also the data were chosen from general company distribution of dairy (Canon company) was proposed test approach and compare; This paper prove that the second proposed approach is better to give the results and satisfy the minimal cost using Q.M. Software

 

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