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Material cost reduction using cutting optimization Pro5 and enhanced N-BEATS deep learning forecasting: a case study
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Manufacturing industry is constantly looking for ways to improve the efficiency of production processes so as to lower production costs, maintain product quality, and improve production planning. This study aims to provide an integrated optimization and forecasting framework that combines Cutting Optimization Pro5, linear programming, and an Enhanced N-BEATS deep learning model to minimize material waste and manufacturing cost and to predict the number of production items with a price-reduction strategy. The real industrial case study is based on production and pricing data from the Akad factory of the General Company for Electrical and Electronic Products in Iraq for the period from 2014 to 2025, concerning the manufacture of 80 L and 120 L electric water heaters. That is, Cutting Optimization Pro5 was used to specify optimal sheet sizes and cutting plans, minimizing waste and reducing production costs. At the same time, the Enhanced N-BEATS deep learning model was implemented to forecast future production quantities. The optimization results showed a significant reduction in wasted materials and production costs, allowing lower product prices. Thus, the forecasting results proved that the performance of the Enhanced N-BEATS model was much better than that of SARIMAX and Simple Linear Regression since the model showed the lowest prediction errors (pMAPE value for the 120 L product is equal to 0.040 and nMSE is equal to 0.016, while pMAPE for the 80 L product equals 0.091, and nMSE equals 0.007). The results show that combining cutting optimization and deep learning can create an efficient decision-support framework to improve production efficiency, lower production costs, and enhance production planning in industrial environments.

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Publication Date
Fri Oct 14 2022
Journal Name
المجلة العراقية لعلوم التربة
REVIEW: USING MACHINE VISION AND DEEP LEARINING IN AUTOMATED SORTING OF LOCAL LEMONS
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Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Publication Date
Sun Jan 01 2017
Journal Name
Green Chemistry
Dissolution of pyrite and other Fe–S–As minerals using deep eutectic solvents
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Processing sulfur containing minerals is one of the biggest sources of acute anthropogenic pollution particularly in the form of acid mine drainage.

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Publication Date
Sun Mar 03 2024
Journal Name
The Science Teacher
Using Scenarios to Assess Student Learning
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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Wed Jan 18 2017
Journal Name
Effect Of Cutting Angle And Knives Type On Some Operational Characteristics For A Locally Manufactured Palm Pruning Motorized Vibration Cutter‏ Aa Jasim, Mr Abbood, Sm Abbood‏
Effect of Cutting Angle and Knives Type on Some Operational Characteristics for a Locally Manufactured Palm Pruning Motorized Vibration Cutter‏
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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
A study of the effect of silica particles addition on some physical properties of PVC as a packaging material
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In this work, varying compositions of SiO2 micro filler were added
with the Polyvinyl Chloride (PVC) and samples have been prepared
using film casting technique. The results have been analyzed and
compared for PVC samples with (1 wt%, 3 wt%, 5 wt% and 10 wt%)
SiO2 micro filler. Mechanical characteristics such as tensile strength,
elongation at break and Young`s modulus were measured for all the
samples, where the tensile strength was increased from 8.39 Mpa for
purified PVC to 16 Mpa for 3% SiO2/PVC composite. Also, thermal
conductivity measurement values illustrated that composite materials
have a good thermal insulation at 10 wt. %, thermal conductivity was
decreased from 0.1684 W/m.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
SBOA: A Novel Heuristic Optimization Algorithm
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A new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Business, Communication & Technology
Exploring the Adoption of Big Data Analytics in the Oil and Gas Industry: A Case Study
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The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company

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Publication Date
Thu Dec 15 2022
Journal Name
Arab World English Journal
Investigating Teachers of English Knowledge and Awareness of Dyslexia: A case study in Primary Iraqi Schools
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Dyslexia is a learning disability in which people face difficulty reading though they are intelligent and have motivation for reading. Therefore; it impacts the portion of the brain responsible for processing language. Such a condition compromises the learning efficiency of the affected person, which generally gets unnoticed. Even affected children are unaware of their state. The study investigates the knowledge and awareness of dyslexia among teachers of English in Iraqi primary schools. this study has three objectives: (i) To investigate the amount of awareness and knowledge among the primary school teachers of English in Baghdad City about dyslexia.; (ii) To examine how English teachers’ awareness of dyslexia is affected by the

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
A Study of the Hydrodynamics Behavior of Cylindrical Gas-Solid Fluidized Beds for pharmaceutical material “Paracetamol “
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The hydrodynamics behavior of gas - solid fluidized beds is complex and it should be analyzed  and understood due to its importance in the design and operating of the units. The effect of column inside diameter and static bed height on the minimum fluidization velocity, minimum bubbling velocity, fluidization index, minimum slugging velocity and slug index have been studied experimentally and theoretically for three cylindrical columns of 0.0762, 0.15 and 0.18 m inside diameters  and 0.05, 0.07 and 0.09 m static bed heights .The experimental results showed that the minimum fluidization and bubbling velocities had a direct relation with column diameter and static bed height .The minimum slugging velocity had an

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