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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
Tue Jan 31 2017
Journal Name
Journal Of Engineering
Sustainable Investment In Architectural Heritage Buildings (Analytical Study Of Arabic Models)
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 Heritage is considered as the civilization and cultural wealth accumulated over the . centuries, whereas architectural heritage is the physical witness of that civilization. Despite the fact that architectural heritage is the most important effort for economic development of any communit,، it suffers from deterioration and neglection especially in the Arab communities. Recently awareness has increased about the importance of investing on architectural heritage generally and sustainable investment particularly. The goal of investment process in heritage areas is to revive economic activity in addition to attempt to revive the heritage and community values. Research aims to examine the relationship between sustainable investment and

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Publication Date
Sun Oct 06 2024
Journal Name
الذكوات البيض
Self-criticism in Quranic models and its impact on building them
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Self-criticism is that a person confronts himself with his mistakes in order to reform and develop them for the better, motivate them and inspire hope in them to push them forward and continue to give in this life. The Holy Qur’an teaches us, through the models it cited in its verses, that this is through repentance, a feeling of remorse, and a determination to leave mistakes, and quit disobedience and sins, etc., and all this is done through constructive criticism, and at the same time, one must realize his strengths. , in order to succeed in preserving it and employing it in the right path that pleases God, His Messenger, himself and his society. This has been explained through an introduction, two topics and a conclusion, and God is t

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Statistical testing mediation in structural equations models variables with practical application
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In this research was the study of a single method of estimation and testing parameters mediating variables (Mediation) in a specimen structural equations SEM a bootstrap method, for the purpose of application of the integrated survey of the situation Marital data and health mirror Iraqi (I-WISH) for the year 2011 from the Ministry of Planning - device Central Bureau of Statistics, and applied to the appropriate data from the terms of the data to a form of structural equation SEM using factor analysis affirmative (Confirmatory Factor analysis) CFA As a way to see the match variables that make up the model, and after confirming the model matching or suitability are having the effect of variables mediation in the model tested by the

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Poisson Regression and Conway Maxwell Poisson Models Using Simulation
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Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.

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Publication Date
Mon Jun 07 2021
Journal Name
Jurnal Teknologi
MODELS, DETECTION METHODS, AND CHALLENGES IN DC ARC FAULT: A REVIEW
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The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha

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Publication Date
Tue Dec 03 2013
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Publication Date
Sun Dec 31 2023
Journal Name
Iraqi Journal Of Information And Communication Technology
EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
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This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

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Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Sun Feb 17 2019
Journal Name
Iraqi Journal Of Physics
Classification of the galaxy Milky Way using variable precision rough sets technique
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Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

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Publication Date
Sun Dec 04 2016
Journal Name
Baghdad Science Journal
Classification of Elliptic Cubic Curves Over The Finite Field of Order Nineteen
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Plane cubics curves may be classified up to isomorphism or projective equivalence. In this paper, the inequivalent elliptic cubic curves which are non-singular plane cubic curves have been classified projectively over the finite field of order nineteen, and determined if they are complete or incomplete as arcs of degree three. Also, the maximum size of a complete elliptic curve that can be constructed from each incomplete elliptic curve are given.

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