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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
Wed Jan 01 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Synthesis of zinc nanoparticles by laser induced plasma and its effects on levels of thyroid hormones
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In the present study, the effect of Zinc nanoparticles on levels of (T3 , T4 and TSH) hormones was investigated. Zinc nanoparticles were synthesized by Laser induced plasma.The Nd: YAG Nd: YAG laser with a wavelength of 1064 nm was used to generate nanomaterials of the elements (zinc) upon collision with target atoms. Plasma generated by different laser intensity is generated. After confirming the preparation of zinc nanoparticles, XRD, AFM was examined, and the effect of these substances on the thyroid gland (T3, T4, TSH) was observed for two doses of each component (1 ml / kg, 4 ml / kg) after conducting a cytotoxicity examination of the lymphocytes of the rats extracted from Rat spleen was 1.8% less toxic to zinc, and as noted The

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Publication Date
Sun Jun 01 2008
Journal Name
Baghdad Science Journal
Plasma Heating of Tokamak by Microwaves at Electron Cyclotron Resonance Heating (ECRH)
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The brief description to the theory of propagation of electromagnetic waves in plasma was done. The cutoff and resonance regions have been showed. The principles of plasma heating at electron cyclotron resonance (ECRH) method have been mentioned. The numerical simulation to three different station: Tosca station in United Kingdom, ISX-B station in USA and T-10 station in Russia had been done. The optical depth and the friction of energy absorbed A have been calculated. The simulation results indicate that both and A are increase with size of the tokamak and it is possible to obtain full absorption in large tokamak.

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Publication Date
Sun Jun 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Steady State Simulation of Atmospheric Crude Distillation Tower
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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression using Hierarchal Linear Polynomial Coding
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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
Visible image watermarking using biorthogonal wavelet transform
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In this paper, visible image watermarking algorithm based on biorthogonal wavelet
transform is proposed. The watermark (logo) of type binary image can be embedded in the
host gray image by using coefficients bands of the transformed host image by biorthogonal
transform domain. The logo image can be embedded in the top-left corner or spread over the
whole host image. A scaling value (α) in the frequency domain is introduced to control the
perception of the watermarked image. Experimental results show that this watermark
algorithm gives visible logo with and no losses in the recovery process of the original image,
the calculated PSNR values support that. Good robustness against attempt to remove the
watermark was s

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Publication Date
Sat Oct 05 2019
Journal Name
Journal Of Engineering And Applied Sciences
Secure Image Steganography using Biorthogonal Wavelet Transform
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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Performance assessment of biological treatment of sequencing batch reactor using artificial neural network technique.
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Artificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa

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Publication Date
Sun Jul 02 2023
Journal Name
Journal Of Pakistan Association Of Dermatologists
The frequency of acute radiodermatitis and associated risk factors among patients with breast cancer treated by radiotherapy
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Background: Acute radiodermatitis is a common side effect during and after radiotherapy course in breast cancer patients treated by radiotherapy. This study assess the frequency of acute radiodermatitis and record the predictive factors for acute radiodermatitis. Patients and Methods: A descriptive case series study conducted at Baghdad, Iraq from August 2020 to September 2021. 70 female scheduled for radiotherapy sessions enrolled in this study. sociodemographic data were recorded and Skin examination before radiotherapy and weekly till the end of the radiotherapy sessions was done to report the frequency, risk factors, clinical picture and grades of acute radiodermatitis based on The National Cancer Institute’s Common Terminology Crite

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Scopus
Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Measuring the Attribute Accuracy and Completeness for the OpenStreetMap Roads Networks for Two Regions in Iraq
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The OpenStreetMap (OSM) project aims to establish a free geospatial database for the entire world which is editable by international volunteers. The OSM database contains a wide range of different types of geographical data and characteristics, including highways, buildings, and land use regions. The varying scientific backgrounds of the volunteers can affect the quality of the spatial data that is produced and shared on the internet as an OSM dataset. This study aims to compare the completeness and attribute accuracy of the OSM road networks with the data supplied by a digitizing process for areas in the Baghdad and Thi-Qar governorates. The analyses are primarily based on calculating the portion of the commission (extr

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