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.
This study includes analytical methods for the determination of the drug amoxicillin trihydrate (Amox.) in some pharmaceutical preparations using Cobalt ion (Co(II)) as complexing metal. The best conditions for complexation were: the reaction time was 20 minutes, pH=1.5 and the best temperature of reaction was 70 ËšC. Benzyl alcohol was the best solvent for extraction the complex.
Keywords: Amoxicillin, Cobalt(II), Complex, Molar ratio.
Roughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are ZH (9.2-13.8) m, Zd (4.3-8.1) m and Zo (0.24-0.48) m.
The main goal of this in vivo study was to evaluate the effect of 532nm Q-switched Nd: YAG Laser in combination with Human Serum Albumin 20% concentration (as a welding aid) on the liver tissue repair clinically, and histologically. The animals used in this study were 21 male rabbits divided into three main groups: control group (3 rabbits), conventionally treated group (9 rabbits) and Laser treated group (9 rabbits). Each two main groups (conventional and laser treated) consist of three sub-groups depending on the response evaluation at three different periods. The Laser group was treated using 532nm Q-switched Nd: YAG laser after adding human serum albumin immediately on the incised liver’s tissue. The energy of was 460mJ, and 4Hz fr
... Show MoreIn this study, the flow and heat transfer characteristics of Al2O3-water nanofluids for a range of the Reynolds number of 3000, 4500, 6000 and 7500 with a range of volume concentration of 1%, 2%, 3% and 4% are studied numerically. The test rig consists of cold liquid loop, hot liquid loop and the test section which is counter flow double pipe heat exchanger with 1m length. The inner tube is made of smooth copper with diameter of 15mm. The outer tube is made of smooth copper with diameter of 50mm. The hot liquid flows through the outer tube and the cold liquid (or nanofluid) flow through the inner tube. The boundary condition of this study is thermally insulated the outer wall with uniform velocity a
... Show MoreCurrently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practica
... Show MoreThe drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the
According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through
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