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A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven classifiers. A hybrid supervised learning system that takes advantage of rich intermediate features extracted from deep learning compared to traditional feature extraction to boost classification accuracy and parameters is suggested. They provide the same set of characteristics to discover and verify which classifier yields the best classification with our new proposed approach of “hybrid learning.” To achieve this, the performance of classifiers was assessed depending on a genuine dataset that was taken by our camera system. The simulation results show that the support vector machine (SVM) has a mean square error of 0.011, a total accuracy ratio of 98.80%, and an F1 score of 0.99. Moreover, the results show that the LR classifier has a mean square error of 0.035 and a total ratio of 96.42%, and an F1 score of 0.96 comes in the second place. The ANN classifier has a mean square error of 0.047 and a total ratio of 95.23%, and an F1 score of 0.94 comes in the third place. Furthermore, RF, WKNN, DT, and NB with a mean square error and an F1 score advance to the next stage with accuracy ratios of 91.66%, 90.47%, 79.76%, and 75%, respectively. As a result, the main contribution is the enhancement of the classification performance parameters with images of varying brightness and clarity using the proposed hybrid learning approach.

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Publication Date
Sat Jul 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Evaluation the Effect of some Plant Extracts in Controlling the Oriental Hornet vespa orientalis Linnaeus, 1771 Near the Apiaries
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Abstract<p>A significant amount of apiaries is destroyed in most areas of Iraq by attacking of the hornet<italic>Vespa orientalis</italic>Linnaeus, 1771, as well as the deterioration of European honey bees’ Apis mellifera Linnaeus, 1758 productivity recently because the environmental changes and pollutions; this effect was evident in the economy and plant production, because the bees as the most popular species of pollinator of crops globally. There is no effective and environmentally safe method yet; Therefore, this study suggested to use essential oils of Mediterranean cypress<italic>Cupressus sempervirens</italic>L., 1753 (Pinales: Cupressaceae), and testing as a repellant substance. In</p> ... Show More
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Publication Date
Mon Apr 01 2019
Journal Name
Biochem. Cell. Arch
Improvement the surface properties of metal valves used in agriculture engine by using CO<inf>2</inf> laser beam
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Protective Effects of Citronellol Against Rhabdomyolysis-Induced Acute Kidney Injury in Mice by Inhibiting NF-κB and IL-1β
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Objectives: acute kidney injury (AKI) is a serious pathophysiology side effect of rhabdomyolysis. Inflammatory mechanisms play a role in the development of rhabdomyolysis-induced AKI. Citronellol (CT) is a naturally occurring monoterpene alcohol (3,7-Dimethyl-6-often-1-ol) found in aromatic plant species' essential oils. In this study, we explored the protective effects of Citronellol on glycerol-induced AKI.

Methods: Four groups of eight mice each (n=8) were formed by randomly dividing the animals into the groups, glycerol-induced AKI model group, low-dose CT-treated group (50mg/kg), high-dose CT-treated group (100mg/kg), and control group. The renal functions of mice from all groups were evalua

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Publication Date
Fri Mar 27 2020
Journal Name
Iraqi Journal Of Science
Study of T-norms and Quantum Logic Functions on BL-algebra and Their Relationships to the Classical Probability Structures
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This paper is concerned with the study of the T-norms and the quantum logic functions on BL-algebra, respectively, along with their association with the classical probability space. The proposed constructions depend on demonstrating each type of the T-norms with respect to the basic probability of binary operation. On the other hand, we showed each quantum logic function with respect to some binary operations in probability space, such as intersection, union, and symmetric difference. Finally, we demonstrated the main results that explain the relationships among the T-norms and quantum logic functions. In order to show those relations and their related properties, different examples were built.

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
Functional Shift of Present and Past Participles from No-minal Meaning to Adjectival Meaning: Функциональная транспозиция причастий в прилагательное
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This paper tackles in detail the functional shift of parts of speech, such as the shift of a verbal clause to an adjectival clause, along with the types of such a shift. The researcher identified the important features of participles, as well as the concept of participles, adjectives, and their types. Also, the most important changes that affect the participles during such shifts. Further, an exposition is made of the different producers through which a verbal clause is changed into an adjectival one in Russian.

      This type of functional shift in parts of speech is seen as a process of deriving most of the new words in contemporary Russian. Russian is very rich in new words, whether by way of processe

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Publication Date
Fri Jul 01 2022
Journal Name
Iraqi Journal Of Science
Modulatory Effects of Date Palm (Phoenix dactylifera L.) Pits Extract Against Ethinylestradiol Induced Genotoxic Damage in Cultured Human Lymphocytes
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Ethinylestradiol is widely used in oral contraceptive formulations and also for the treatment of various sexual and metabolic disorders. It is not only a genotoxic agent but also a tumor initiating agent. In the present study, the modulatory effect of aqueous extract of date pits was evaluated against the genotoxic effect induced by ethinylestradiol on human lymphocytes using chromosomal aberrations (CA), blast index (BI), mitotic index (MI), sister chromatid exchanges (SCE) and replication index (RI) as parameters. The date pits extract was evaluated at 1.075x10-4, 2.125x10-4, 3.15x10-4 and 4.17x10-4 g/ml along with 10 μM of ethinylestradiol in culture medium. The results showed a significant dose-dependent decrease in the frequency of

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Create sustainable value to the customer through the integration of the relationship between total quality management and relationship marketing
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Purpose: This research seeks to provide a point of view based on the creation of sustainable value to the customer of the banks in the context of total quality management and relationship marketing. It aims to develop a model to measure the value of sustainable customer peduncular under total quality management PAL (administrative leadership, involvement of employees, continuous improvement, process improvement, staff training), through the mediation of relationship marketing and objective dimensions (administrative leadership, involvement of employees, continuous improvement, improving processes , staff training), and to explore any of the variables and dimensions more influential in the creation of sustainable value to the cust

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Publication Date
Mon Mar 02 2009
Journal Name
Albahith Alalami
Types, contents and scientific research methods used in public relations research at the College of Mass Communication 1989 - 2007.
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This study deals with knowing the types of research in public relations studies at the Faculty of Mass Communication for the period from 1989 to 2007 and knowing the methods that researchers used in their studies, as well as knowing the methods and tools of scientific research that were used, and whether one method or tool is used more than others, and knowing Samples used in the analysis. As well as the contents and types of this research The institutions that were subjected to the study, and the preparation of the respondents This research aims to answer the following questions:. A- What are the types of research and methods that were used in university theses that dealt with the topic? Public Relations at the Faculty of Media from 1989

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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