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Classification of Apple Slices Treated by Atmospheric Plasma Jet for Post-harvest Processes Using Image Processing and Convolutional Neural Networks
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Abstract<p>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.</p>
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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Tue Feb 02 2010
Journal Name
Advances In Software Engineering
A Strategy for Automatic Quality Signing and Verification Processes for Hardware and Software Testing
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We propose a novel strategy to optimize the test suite required for testing both hardware and software in a production line. Here, the strategy is based on two processes: Quality Signing Process and Quality Verification Process, respectively. Unlike earlier work, the proposed strategy is based on integration of black box and white box techniques in order to derive an optimum test suite during the Quality Signing Process. In this case, the generated optimal test suite significantly improves the Quality Verification Process. Considering both processes, the novelty of the proposed strategy is the fact that the optimization and reduction of test suite is performed by selecting only mutant killing test cases from cumulating t-way test ca

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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Energy Consumption Analyzing in Single hop Transmission and Multi-hop Transmission for using Wireless Sensor Networks
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Wireless sensor networks (WSNs) are emerging in various application like military, area monitoring, health monitoring, industry monitoring and many more. The challenges of the successful WSN application are the energy consumption problem. since the small, portable batteries integrated into the sensor chips cannot be re-charged easily from an economical point of view. This work focusses on prolonging the network lifetime of WSNs by reducing and balancing energy consumption during routing process from hop number point of view. In this paper, performance simulation was done between two types of protocols LEACH that uses single hop path and MODLEACH that uses multi hop path by using Intel Care i3 CPU (2.13GHz) laptop with MATLAB (R2014a). Th

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Optical Forward Scattering Property Employment for measuring the Atmospheric Visibility
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Abstract
An optoelectronic system for fog detection and visibility technique is presented .The idea of this research is based on the measurement of the atmospheric visibility by using an infrared beam emitter from LED diode. The optical scattering is used as a method to calculate the visibility. This method is applied at forward scattering within a foggy atmosphere, which is modern and has great importance for measuring visibility in seaports, airports, public roads and highways. In this paper we focus on the description of the system, principles of its operation and some results of field tests.
Keywords: fog sensor, visibility sensor, backscattering, forward scattering.

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Publication Date
Tue Apr 02 2024
Journal Name
Journal Of Engineering
Revolutionizing Depth Sensing: A Review Study of Apple LiDAR Sensor for as-built Scanning Applications
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Incorporating the LiDAR sensor in the most recent Apple devices represents a substantial development in 3D mapping technology. Meanwhile, Apple's Lidar is still a new sensor. Therefore, this article reviews the potential uses of the Apple Lidar sensor in various fields, including engineering and construction, focusing on indoor and outdoor as-built 3D mapping and cultural heritage conservation. The affordable cost and shorter observation times compared to traditional surveying and other remote sensing techniques make the Apple Lidar an attractive choice among scholars and professionals. This article highlights the need for continued research on the Apple LiDAR sensor technology while discussing its specifications and limitations. A

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Publication Date
Sat Aug 31 2019
Journal Name
Iraqi Journal Of Physics
Spectroscopic Diagnostic of Cadmium Sulfide Plasma Produced By LIBS
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Abstract

       The current study was carried out to reveal the plasma parameters such as ,the electron temperature ( ), electron density (ne) , plasma frequency (fp), Debye length ( ) , Debye number (   for  CdS to employ the LIBS for the purpose of analyzing and determining spectral emission lines using . The results of electron temperature for CdS range (0.746-0.856) eV , the electron density(3.909-4.691)×1018 cm-3. Finally ,we discuss plasma parameters of CdS  through  nano second  laser generated plasma .

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Sat Apr 01 2023
Journal Name
Science Of The Total Environment
Recent advances and applicable flexibility potential of electrochemical processes for wastewater treatment
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This study examined >140 relevant publications from the last few years (2018–2021). In this study, classification was reviewed depending on the operation's progress. Electrocoagulation (EC), electrooxidation (EO), electroflotation (EF), electrodialysis (ED), and electro-Fenton (EFN) processes have received considerable attention. The type of action (individual or hybrid) for each electrochemical procedure was evaluated, and statistical analysis was performed to compare them as a new manner of reviewing cited papers providing a massive amount of information efficiently to the readers. Individual or hybrid operation progress of the electrochemical techniques is critical issues. Their design, operation, and maintenance costs vary depending o

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Publication Date
Wed Jan 01 2020
Journal Name
دار الكتب والوثائق العراقيه
Essentilas of Atmospheric Sciences - ISBNiraq.org
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Essentilas of Atmospheric Sciences - ISBNiraq.org

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Publication Date
Thu Jun 10 2021
Journal Name
Neuroquantology
Global Effects of Atmospheric Emissions
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The element carbon Carbon dioxide emissions are increasing primarily as a result of people's use of fossil fuels for electricity. Coal and oil are fossil fuels that contain carbon that plants removed from the atmosphere by photosynthesis over millions of years; and in just a few hundred years we've returned carbon to the atmosphere. The element carbon Carbon dioxide concentrations rise primarily as a result of the burning of fossil fuels and Freon for electricity. Fossil fuels such as coal, oil and gas produce carbon plants that were photosynthesized from the atmosphere over many years, since in just two centuries, carbon was returned to the atmosphere. Climate alter could be a noteworthy time variety in weather designs happening ov

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