Maintaining the quality of apricot fruits during storage is not an easy task due to the changes in their physical and chemical properties, so it is necessary to use less expensive, easy to apply, environmentally friendly, and safer preservatives to maintain the nutritional value of apricot. The damage to some fruits during storage can be a source of infection, which leads to the damage of healthy fruits more quickly, which requires building an intelligent model to detect damaged fruits. The aim of the research is to study the effect of immersing apricots in lemon juice once and sugar-water solution again on the quality properties of apricots, including sweetness, color, hardness, and water content. On the other hand, the YOLOv7 algorithm was used to detect healthy fruits and damaged areas using a camera. The results showed that sweetness increased with increasing immersion time in sugar-water solution to reach 22.1 Brix, while it decreased with increasing immersion time in lemon juice to 19.12 Brix. Also, hardness increased with increasing immersion time in sugar-water solution to reach 3.7 kg/cm2. The water content of apricots decreased with increasing immersion time in different immersion media from 77.14 g to 73.93 g. In addition, CIE-L*a*b levels increased with increasing immersion time in different immersion media. For the performance indicators of the YOLOv7 algorithm, precision of 84.5%, recall of 87%, F1 of 0.77, and [email protected] of 77.2 were obtained, respectively. Therefore, this study is expected to reduce the workload in post-harvest fruit processing and help in the rapid identification and detection of damaged fruits based on smart detection algorithms, thus improving sorting efficiency and reducing both waste and economic losses, which enhances smart agriculture technologies.
Many stone tools were found on a hill south of the Hor Al-Dalmaj which is located in the central part of the alluvial plain of Mesopotamia, between the Tigris and Euphrates Rivers. The types of rocks from which the studied stone tools were made are not found in the alluvial plain, because it consists of friable sand, silt, and clay. All existing sediments were precipitated in riverine environments such as point bar, over bank, and floodplain sediments. The collected stone tools were described with a magnifying glass (10 x) and a polarized microscope after they were thin sectioned. Microscopic analysis showed that these stone tools are made of sedimentary, volcanic igneous and metamorphic rocks, such as: sandstones, limestones, chert, con
... Show Morecontent Analysis for Some Type of Pillows used in Iraqi houses
Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable
... Show MoreThe applications of Multilevel Converter (MLC) are increased because of the huge demand for clean power; especially these types of converters are compatible with the renewable energy sources. In addition, these new types of converters have the capability of high voltage and high power operation. A Nine-level converter in three modes of implementation; Diode Clamped-MLC (DC-MLC), Capacitor Clamped-MLC (CC-MLC), and the Modular Structured-MLC (MS-MLC) are analyzed and simulated in this paper. Various types of Multicarrier Modulation Techniques (MMTs) (Level shifted (LS), and Phase shifted (PS)) are used for operating the proposed Nine level - MLCs. Matlab/Simulink environment is used for the simulation, extracting, and ana
... Show MoreIn the present work a dynamic analysis technique have been developed to investigate and characterize the quantity of elastic module degradation of cracked cantilever plates due to presence of a defect such as surface of internal crack under free vibration. A new generalized technique represents the first step in developing a health monitoring system, the effects of such defects on the modal frequencies has been the main key quantifying the elasticity modulii due to presence any type of un-visible defect. In this paper the finite element method has been used to determine the free vibration characteristics for cracked cantilever plate (internal flaws), this present work achieved by different position of crack. Stiffness re
... Show MoreAntibacterial substances belong to a group of compounds that attack dangerous microorganisms. Therefore, killing bacteria or reducing their metabolic activity will lessen their adverse effects on a biological system. They originated from either synthetic materials, microbes, or mold. Many of these medications treat the gram-negative bacteria from the critical precedence group, such as pseudomonas, carbapenem-resistant acinetobacter, and enterobacterales. This study aims to investigate the simultaneous analysis of specific antibacterial spectrophotometrically. The WHO maintains this list of priority infections with antibiotic resistance. Drug combinations in single dosage forms are becoming increasingly popular in the pharmaceutical industry
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func
In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha
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