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.
Today, urban Stormwater management is one of the main concerns of municipalities and stakeholders. Drought and water scarcity made rainwater harvesting one of the main steps toward climate change adaptation. Due to the deterioration of the quality of urban runoff and the increase of impermeable urban land use, the treatment of urban runoff is essential. Best Management Practice (BMP) and Low Impact Development (LID) approaches are necessary to combat climate change consequences by improving the quantity and quality of water resources. The application of Bioswales along urban streets and roadways can reduce the stress on water resources, recharge groundwater and prevent groundwater pollution. While Sulaymaniyah City has a
... Show MoreThis paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor
... Show MoreThe research topic was chosen as a result of the importance of human resource in business organizations in general and the industrial process in particular. Without the human resource, business organizations cannot continue and achieve success and excellence, and the research problem has been diagnosed in the lack of sales of General Cement Company’s northern products, despite their distinctiveness, standing, and reputation in The market and its products with standard specifications, and through this problem, the following questions were raised: &nbs
... Show MoreThe aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting
... Show MoreThe present study identifies the linguistic means used to realize hyperbole in poetry as a rhetorical device that makes readers experience the beauty of poetic language. To achieve the aim of the study, a model of analysis in accordance with Spitzbardt (1963), Norrick (1982), and McCarthy & Carter (2004) is used. The analysis of data under investigation reveals that hyperbole is a crucial aid used by poets to portrait the real world as imaginative. In conclusion, poets prefer using lexico-grammatical repertoires than lexico-grammatical configurations. Keywords
The research aims to improve the performance of the Directorate of Maysan water by reconciling the objectives of the employees of the directorate with the objectives of the Directorate itself, as well as to identify the strengths and weaknesses in the performance of the Directorate (Leadership - Individuals - Knowledge - Operations - Financial) and presented to experts and arbitrators of specialized, and the researchers have relied on the case study methodology as a descriptive approach is comprehensive analysis, and draws on more than one approach, method and scientific design, has been interviewed a number of experts in the Directorate Maysan's water Identify the weaknesses and strengths of the Directorate, the research has rea
... Show MoreAbstract Iraq has an important place in the regional and international balance, and the competition among countries has increased in rapprochement with Iraq, not only for its geography or its privileged location, but because it has many other components that make regional and international countries want to strengthen their relations with it (Regional and international powers). In addition to that, Iraq has become increasingly important for these international and regional powers after its victory over the terrorist organization (ISIS), which proved an important fact that Iraq represents the most important pillars in the international balance.
In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the
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