Apple slice grading is useful in post-harvest operations for sorting, grading, packaging, labeling, processing, storage, transportation, and meeting market demand and consumer preferences. Proper grading of apple slices can help ensure the quality, safety, and marketability of the final products, contributing to the post-harvest operations of the overall success of the apple industry. The article aims to create a convolutional neural network (CNN) model to classify images of apple slices after immersing them in atmospheric plasma at two different pressures (1 and 5 atm) and two different immersion times (3 and again 6 min) once and in filtered water based on the hardness of the slices using the k-Nearest Neighbors (KNN), Tree, Support Vector Machine (SVM), and Artificial Neural Network (ANN) algorithms. The results showed an inverse relationship between the storage period and the hardness of the apple slices, with the average hardness values gradually decreasing from 4.33 (day 1) to 3.37 (day 5). Treatment with atmospheric plasma at a pressure of 5 atm and an immersion time of 3 min gave the best results for maintaining the hardness of the slices during the storage period, recording values of 4.85 (first day) and 3.68 (fifth day), outperforming other treatments. The average improvement rate was 23.09% over five consecutive days. Regarding the CNN algorithms, the ANN algorithm achieved the highest classification accuracy of 97%, while the Tree algorithm achieved the lowest accuracy of 88.7%. The KNN and SVM algorithms achieved classification accuracies of 94.7% and 95.1%, respectively. The study demonstrated the possibility of using a CNN to classify apple slices based on the degree of hardness. Furthermore, the application of atmospheric plasma at 5 atmospheres with a 3-min immersion improves the firmness of the apple slices by inhibiting degradative enzymes while preserving the cellular structure and tissue quality.
This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe
... Show MoreMachine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
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Objectives: The study is carried out to assess functional performance for heart's valve replacement patients and find out relationship with sociodemographic data and clinical data
Methodology: Descriptive design is carried out at cardiac surgery centers in Baghdad ; Ibn -Al Betar Specialized for cardiac surgery center and Al-Iraqi center for cardiac disease. its initiation from December28the 2013 to September 1st 2014,A non- probability (purposive) sample of 50 adults patients are attended cardiac surgery centers at Baghdad city and who have heart valves replacement. The data collection through development of questionnaire which is composed from three parts(socio demographic data, clinical information, functional performa
Background: The purpose of this study was to compare regional bond strength at middle and cervical thirds of the root canal among glass fiber-reinforced composite (FRC) endodontic posts cemented with different cements, using the push-out test to compare the performance (retention) of two types of luting cements; polycarboxylate cement and Zinc phosphate cement used to cement translucent fiber post and to compare the result of the push-out test at different storage times;1 week ,1month and 2 months. Materials and methods: Ninety caries-free, recently extracted single-rooted human teeth with straight root canals was used in this study, The root canals were endodontically instrumented at a working length of 0.5 mm from the apex by m
... Show MoreObjectives: To determined the levels of lipid profile (TC, TG, HDL-c, LDL-C, VLDL) in diabetic and diabetic neuropathy patients and compare the results with control group. Also, to compare Atherogenic Index of Plasma (AIP) levels in these groups that may be predict prone of patients to cardiovascular disease. Methodology: Ninety subjects were enrolled in this study with aged ranged (40-65) years and BMI with (30-35) Kg/m2 that divided into three groups as follows: group one (G1) consists of 30 healthy individuals as a control group, group two (G2) consists of 30 patients with diabetes and group three (G3) consists of 30 patients with diabetes and neuropathy as complication. Electrochemical Skin Conductance (Feet Mean), Electrochemic
... Show MoreThe holmium plasma induced by a 1064-nmQ-switched Nd:YAG laser in air was investigated. This work was done theoretically and experimentally. Cowan code was used to get the emission spectra for different transition of the holmium target. In the experimental work, the evolution of the plasma was studied by acquiring spectral images at different laser pulse energies (600,650,700, 750, and 800 mJ). The repetition rates of (1Hz and 10Hz) in the UV region (200-400 nm). The results indicate that, the emission line intensities increase with increasing of the laser pulse energy and repetition rate. The strongest emission spectra appeared when the laser pulse energy is 800mJ and 10 Hz repetition rate at λ= 345.64nm, with the maximum intensi
... Show MoreExplanation of article events , or discribing it establish to anderstanding an phenomenon which its effects still clear in the art , surching like this may be very usful in the analysis of new art , which considering one of the most important turns in the history of art . and if we look to human body in the art as existenc in the art , from it’s begening to the modern age . so we can understand the meaning of this existence and it’s directins which cover all the worid and the lead us to thiories and suggestion’s help in understand to this direction and the effects between our arts and the external directions.
For the time being, the cold-formed sections are widely used due to their simple manufacturing and construction processes. To be feasible, the strength of cold-formed columns should be determined based on their post-buckling behavior. Post-buckling relations are cumbersome and need design aids similar to those of American Iron and Steel Institute (AISI) to be applicable. These design aids have been developed to sections and materials other than those available in the local market. Therefore, this paper tries to develop a general finite element model to simulate the postbuckling behavior of cold-formed steel columns. Shell element has been used to discretize the web, flanges, and lips of the column. A linear bucking analy
... Show MoreTo ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib
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