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bsj-5159
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage and Selection Operator (Lasso), and Tikhonov Regularization (Ridge). The simulation studiesshow that the performance of our method is better than the othersaccording to the error and the time complexity. Thesemethodsare applied to a real dataset, which is called Rock StrengthDataset.The new approach implemented using the Gibbs sampler is more powerful and effective than other approaches.All the statistical computations conducted for this paper are done using R version 4.0.3 on a single processor computer.

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Publication Date
Thu Feb 11 2016
Journal Name
Journal Of Materials Science: Materials In Electronics
Electrochemical deposition of CdSe-sensitized TiO2 nanotube arrays with enhanced photoelectrochemical performance for solar cell application
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Classification of Diseases in Oil Palm Leaves Using the GoogLeNet Model
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The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

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Publication Date
Sat Mar 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Selection of Suitable Drilling Parameters for obtaining high Rate of Penetration in Majnoon Oilfield
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Several directional wells have been drilled in Majnoon oilfield at wide variation in drilling time due to different drilling parameters applied for each well. This technical paper shows the importance of proper selection of the bit, Mud type, applied weight on Bit (WOB), Revolution per minute (RPM), and flow rate based on the previous wells drilled. Utilizing the data during drilling each section for directional wells that's significantly could improve drilling efficiency presented at a high rate of penetration (ROP). Based on the extensive study of three directional wells of 35 degree inclination (MJ-51, MJ-52, and MJ-54) found that the applied drilling parameters for MJ-54 and the bit type within associated drilling parameters to drill

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Fri May 15 2015
Journal Name
Euphrates Journal Of Agricultural Science
Performance Evaluation of field and genetic for genotype selection from Tomato Lycopersicon esculeuntum Mill.
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The study was conducted at the fields of the Department of Horticulture and Landscape Gardening,College of Agriculture, University of Baghdad during the growing seasons of 2013- 2014 .forPerformance of Evaluation Vegetative growth and yield traits and estimate some important geneticparameter on seven selected breed of tomato which (S1-S7 ) Pure line. the results found significantdifferences between breeds in all study trails except clusters flowering number .S1 significantly plantlength which reached 227.3 .Also S1,S2 and S4 were significantly increased the number fruit for plant,Fruit weight Increased in S3 ,S6 and plant yield. Increased in S1, S4 ,S5. Genetic variation valueswere low in Floral clusters , TSS and fruit firmest and medium i

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Publication Date
Thu Jul 03 2025
Journal Name
Circular Economy And Sustainability
Green Supplier Selection in the Iraqi Food Industry: Criteria Analysis and Barriers to Implementation
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This study explores the barriers to adopting green environmental criteria in Supplier Selection (SS) within the Iraqi food industry. It aims to enhance the understanding of sustainable supply chain management in developing nations, with a particular focus on the Iraqi context. A case study approach was utilized to identify eleven key green environmental criteria and 54 sub-criteria, alongside seven major barriers to their adoption. The Best–Worst Method (BWM) was employed to rank the criteria, and Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) was used to prioritize the barriers. The analysis revealed that Environmental Management Systems are the most critical criterion for SS. On the other hand, legislation and policies emerged

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Publication Date
Sat May 30 2020
Journal Name
Neuroquantology Journal
The Effect of Re-Use of Lossy JPEG Compression Algorithm on the Quality of Satellite Image
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In this study, an analysis of re-using the JPEG lossy algorithm on the quality of satellite imagery is presented. The standard JPEG compression algorithm is adopted and applied using Irfan view program, the rang of JPEG quality that used is 50-100.Depending on the calculated satellite image quality variation, the maximum number of the re-use of the JPEG lossy algorithm adopted in this study is 50 times. The image quality degradation to the JPEG quality factor and the number of re-use of the JPEG algorithm to store the satellite image is analyzed.

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Publication Date
Thu Nov 17 2016
Journal Name
Plos One
Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network
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Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destina

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Publication Date
Thu Feb 13 2020
Journal Name
International Journal Of Environmental Research
Synthesis of a Novel Composite Sorbent Coated with Siderite Nanoparticles and its Application for Remediation of Water Contaminated with Congo Red Dye
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Abstract

Re-use of the byproduct wastes resulting from different municipal and industrial activities in the reclamation of contaminated water is real application for green projects and sustainability concepts. In this direction, the synthesis of composite sorbent from the mixing of waterworks and sewage sludge coated with new nanoparticles named “siderite” (WSSS) is the novelty of this study. These particles can be precipitated from the iron(II) nitrate using waterworks sludge as alkaline agent and source of carbonate. Characterization tests using X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) mapping revealed that the coating process was c

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Predicting Social Security Fund compensation in Iraq using ARMAX Model
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Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ

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