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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. Furthermore, the major objective was to formulate a deep learning model for the identification of diseases and pests affecting oil palm leaves, using image analysis techniques to facilitate pest management practices. To address the core problem under investigation, the GoogLeNet deep learning approach was applied, alongside various hyperparameters. The classification experiments were executed across 16 trials, each capped at a computational timeframe of 10 minutes, and the predominant duration spanned from 2 to 7 minutes. The results, particularly derived from the superior performance in Model 4 (M4), showed evaluation accuracy, precision, recall, and F1-score rates of 93.22%, 93.33%, 93.95%, and 93.15%, respectively. These were highly satisfactory, warranting their application in oil palm companies to enhance the management of pest and disease attacks.

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Publication Date
Sun May 22 2022
Journal Name
International Journal Of Early Childhood Special Education
The impact of using learning acceleration model on the achievement of mathematics for third intermediate grade students
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The current study aims at identifying the impact of using learning acceleration model on the achievement of mathematics for third intermediategrade students. Forachieving this, the researchers chose the School (Al-Kholood Secondary School for Girls) affiliated to the General Directorate of Babylon Education / Hashemite Education Department for the academic year (2021/2021), The sample reached to (70) female students from the third intermediate grade, with (35) female students for each of the two research groups. The two researchers prepared an achievement test consisting of (25) objective items of multiple choice type, The psychometric properties of the test were confirmed, and after the completion of the experiment, the achievement test wa

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Study of the matter density distributions of halo nuclei 6He and 16C using the binary cluster model
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The harmonic oscillator (HO) and Gaussian (GS) wave functions within the binary cluster model (BCM) have been employ to investigate the ground state neutron, proton and matter densities as well as the elastic form factors of two- neutron 6He and 16C halo nuclei. The long tail is a property that is clearly revealed in the density of the neutrons since it is found in halo orbits. The existence of a long tail in the neutron density distributions of 6He and 16C indicating that these nuclei have a neutron halo structure. Moreover, the matter rms radii and the reaction cross section (𝜎𝑅 ) of these nuclei have been calculated using the Glauber model.

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Publication Date
Tue Oct 19 2021
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Object Tracking Using Adaptive Diffusion Flow Active Model
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Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Agile manufacturing assessment model using multi-grade evaluation
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In unpredicted industrial environment, being able to adapt quickly and effectively to the changing is key in gaining a competitive advantage in the global market. Agile manufacturing evolves new ways of running factories to react quickly and effectively to changing markets, driven by customized requirement. Agility in manufacturing can be successfully achieved via integration of information system, people, technologies, and business processes. This article presents the conceptual model of agility in three dimensions named: driving factor, enabling technologies and evaluation of agility in manufacturing system. The conceptual model was developed based on a review of the literature. Then, the paper demonstrates the agility

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Euro Dinar Trading Analysis Using WARIMA Hybrid Model
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The rise in the general level of prices in Iraq makes the local commodity less able to compete with other commodities, which leads to an increase in the amount of imports and a decrease in the amount of exports, since it raises demand for foreign currencies while decreasing demand for the local currency, which leads to a decrease in the exchange rate of the local currency in exchange for an increase in the exchange rate of currencies. This is one of the most important factors affecting the determination of the exchange rate and its fluctuations. This research deals with the currency of the European Euro and its impact against the Iraqi dinar. To make an accurate prediction for any process, modern methods can be used through which

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Publication Date
Thu Jan 21 2021
Journal Name
Recent Innovations In Chemical Engineering (formerly Recent Patents On Chemical Engineering)
Soap Production Using Vacuum Reactive Distillation: Batch Model
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Introduction: Although soap industry is known from hundreds of years, the development accompanied with this industry was little. The development implied the mechanical equipment and the additive materials necessary to produce soap with the best specifications of shape, physical and chemical properties. Objectives: This research studies the use of vacuum reactive distillation VRD technique for soap production. Methods: Olein and Palmitin in the ratio of 3 to 1 were mixed in a flask with NaOH solution in stoichiometric amount under different vacuum pressures from -0.35 to -0.5 bar. Total conversion was reached by using the VRD technique. The soap produced by the VRD method was compared with soap prepared by the reaction - only method which

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Publication Date
Fri Jul 28 2017
Journal Name
Iraqi Journal Of Science
3D Building Reconstruction Using DEM and Mosaic Model
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A digital elevation model (DEM) is a digital representation of ground surface topography or terrain. It can be represented as a raster (a grid of squares) and it is commonly estimated by utilizing remote sensing techniques, or from land surveying. In this research a 3D building of Baghdad university campus have been performed using DEM, where the easting, northing, and elevation of 400 locations have been obtained by field survey using global positioning system (GPS). The image of the investigated area has been extracted from QuickBird satellite sensor (with spatial resolution of 0.6 m). This image has been geo-referenced by selecting ground control points of the GPS. The rectification is running, using 1st order polynomial transformation.

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Study the Effect of Catalyst -to- Oil Ratio Parameter (COR) on Catalytic Cracking of Heavy Vacuum Gas Oil
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This work deals with the production of light fuel cuts of (gasoline, kerosene and gas oil) by catalytic cracking treatment of secondary product mater (heavy vacuum gas oil) which was produced from the vacuum distillation unit in any petroleum refinery. The objective of this research was to study the effect of the catalyst -to- oil ratio parameter on catalytic cracking process of heavy vacuum gas oil feed at constant temperature (450 °C). The first step of this treatment was, catalytic cracking of this material by constructed batch reactor occupied with auxiliary control devices, at selective range of the catalyst –to- oil ratio parameter (  2, 2.5, 3 and 3.5) respectively.  The conversion of heavy vacuum gas

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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Agriculture And Crops
Distribution and Classification of Medicinal Plants in Zakhikhah Area of Al-Anbar Desert
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This study included the Zakhikhah area in the Al- Anbar desert, which it bounded on the north, east, and west by the Euphrates River and on the south by the Ramadi-Qaim road. Several exploratory field trips were taken to the study area. During this time, a semi-detailed area survey was carried out based on satellite imagery captured by American Land sat-7, topographic maps, and natural vegetation variance. All necessary field tools, including a digital camera and GPS device, were brought to determine the soil type and collect plant samples. All of these visits are planned to cover the entire state of Zakhikhah. All vegetation cover observations, identifying sampling sites and attempting to inventory and collect medicinal plants in t

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Publication Date
Thu Jun 06 2024
Journal Name
Journal Of Applied Engineering And Technological Science (jaets)
Deep Learning and Its Role in Diagnosing Heart Diseases Based on Electrocardiography (ECG)
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Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

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