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Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the SVM-polynomial algorithm, while the lowest 86.66% by LDA algorithm. The SVM-linear also has an accuracy of 90%. The study showed how machine learning algorithms can be used to classify banana slices according to their sweetness.

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Sun Feb 27 2022
Journal Name
Iranian Journal Of Ichthyology
Production of peptide antibiotic bacteriocin using banana peel media
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Many strains of lactic bacteria produce antimicrobial peptides of bacteriocins that are antibiotics used against pathogenic strains. The present work aimed to use a banana peels medium in the fermentation process to replace the commercial MRS medium for decreasing the cost of bacteriocins LAB production. Based on the result, banana peel was a cost-effective and viable alternative carbon source for the production and development of bacteriocin-producing Lactobacilli. The growth of lactobacilli in commercial MRS medium and Banana Peel medium showed no differences, therefore banana peel waste can be used to produce Lactobacilli bacteriocins. Lactobacillus strains grew exceptionally well at 37 C and pH 6.0.

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Partial Purification and Characterization of Catalase from Banana Peels
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Catalase (EC 1.11.1.6) is a well known enzyme which exists in almost all living creatures exposing to oxygen (such as plants, bacteria, and animals). It is a very necessary enzyme to protect the cell from oxidative detriment by reactive oxygen species (ROS). The aim of this study is the partial purification and characterization of Catalase enzyme from Banana peels. In this study, fresh banana peels are treated with 70 % ethanol ,further separated with chloroform ,water and ethyl acetate respectively .The supernatant of the enzymatic sample which is treated with chloroform is loaded into gel filtration column with Sephadex G-100 (1.0 x 90 cm) equilibrated with pH7 buffer media (phosphate buffer 0.1 M). Kinetic studies of the purified en

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Fri Jul 30 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm
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The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
A comparison between banana peel powder and gel for removing methylene blue dye from aqueous solution
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This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Fabrication of Advanced Cement Mortar for Building Anti-Bacterial Applications
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In this research, we have added nano anatase TiO2 as a partial replacement of Portland cement by a weight percentage of (0.25 to 1%) for the development of properties for protection against bacteria. The control mix was made by using "the cement to sand" proportion about (1: 2.75) with the "water to cement" proportion of (0.5) to study the structure, porosity, water absorption, density, mechanical properties, as well as anti-bacterial behavior. Inspections have been done such as scanning electron microscopy (SEM), and atomic force microscope (AFM) for mortar. Experimental results showed that after the addition of Nano powders in cement mortar, the structural properties improved significantly with the development of hydration o

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