The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a comparative study of the algorithms in order to determine which algorithm has the highest prediction accuracy. The results showed that the value of the red color has a greater effect than the green and blue colors in predicting the sweetness of orange fruits, as there is a direct relationship between the value of the red color and the level of sweetness. In addition, the logistic regression model algorithm gave the highest degree of accuracy in predicting sweetness.
Abstract:
There is a close relationship between rigidity and distort structure of production and productivity and inflation rates. The effects of this relationship are distorted the contribution rate of the productive sectors and the disproportionate of exchange rate in foreign trade.
raising the general level of prices is one of the way that have been used by previous governments (inflationary financing or deficit financing) in order to speed up the process of capital formation, depending on the availability of economic resources idle.
The fabricating inflation for development does not represent a true understanding of the nature of the
... Show More This paper concerns with openness concept in contemporary learning environment, which ranges from physical characters to its relation with learning efficiency and its output. Previous literatures differ to clear the effect of openness on the engagement between learner within themselves, and with this kind of spaces. Engagement means: active participation, the ability of making dialogue, self-reflection and the ability to explore and communicate with them and
within learning space. Research roblem was: The lack of knowledge about the effect of Openness on learner engagement with learning spaces. The two concepts were applied on three types of learning spaces in the Department of the Architectu
Background:Periodontal diseases are infectious diseases in which periodontalpathogens trigger chronic inflammatory and immune responses. Interleukine-6 is a multifunctional cytokine playing a central role in inflammation and tissue injury.The aim of the study IS to determine the level of Interleukin-6(IL-6) in saliva of patients with chronic periodontitis compared to healthy subjects. Materials and Methods:The total subjects of the present study is 60, divided into 3 groups; 20 patients with chronic periodontitis with pocket depth(PD ≥4 mm)(group I), 20 patients with pocket depth(PD <4 mm) with clinical attachment loss (group II), and 20 healthy controls with pocket probing depth (PPD ≤ 3 mm) without clinical attachment loss (g
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The research aims to analyze the value chain of dairy products in Iraq (Abu Ghraib/Study Case) factories for the year 2022, where value chain rings are identified to discuss and track the most important determinants and problems in the value chain rings of dairy products and their basic and secondary activities, as well as calculate the value added of the products by subtracting the total revenues of products from their variable costs. Research data were collected for the period 2022. Preliminary information and data from its field sources and personal interviews were collected through a questionnaire prepa
The Karolinka earth-fill dam was constructed between 1977 and 1984 on the Stanovnice river above the town of Karolinka in the region of Vsetínsko in Czech Republic. Because of leakage on the downstream dam face due to technological indiscipline when filling dam layers during the dam construction stage, there were some steps to improve state dam safety. The final rehabilitation is to construct the diaphragm walls from self-hardening cement-bentonite suspension along the length of the dam. In addition to connecting the gallery and abutment (2 × 25 m long) by using jet piles. The article presents numerical modeling of safety factor evaluation associated with the state of the dam body and foundation; before, and after seal
... Show MoreCorrect grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
... Show MoreHeart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac
... Show MoreThis study aims to employ modern spatial simulation models to predict the future growth of Al-Najaf city for the year 2036 by studying the change in land use for the time period (1986-2016) because of its importance in shaping future policy for the planning process and decision-making process and ensuring a sustainable urban future, using Geographical information software programs and remote sensing (GIS, IDRISI Selva) as they are appropriate tools for exploring spatial temporal changes from the local level to the global scale. The application of the Markov chain model, which is a popular model that calculates the probability of future change based on the past, and the Cellular Automa
Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate
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