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Fast Shot Boundary Detection Based on Separable Moments and Support Vector Machine

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

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Publication Date
Wed Sep 07 2022
Journal Name
2022 Iraqi International Conference On Communication And Information Technologies (iiccit)
Construct an Efficient DDoS Attack Detection System Based on RF-C4.5-GridSearchCV

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Fast Processing RNA-Seq on Multicore Processor

RNA Sequencing (RNA-Seq) is the sequencing and analysis of transcriptomes. The main purpose of RNA-Seq analysis is to find out the presence and quantity of RNA in an experimental sample under a specific condition. Essentially, RNA raw sequence data was massive. It can be as big as hundreds of Gigabytes (GB). This massive data always makes the processing time become longer and take several days. A multicore processor can speed up a program by separating the tasks and running the tasks’ errands concurrently. Hence, a multicore processor will be a suitable choice to overcome this problem. Therefore, this study aims to use an Intel multicore processor to improve the RNA-Seq speed and analyze RNA-Seq analysis's performance with a multiproce

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
A Direct Solution Scheme for Wide-Angle Electromagnetic Scattering Problems Using Compressive Sensing-Based Method of Moments

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Publication Date
Fri Nov 01 2013
Journal Name
Isesco Journal Of Science And Technology
Effect of Solvents on the Dipole Moments and Fluorescence Quantum Yield of Rhodamine Dyes

Abstract: This study aims to investigate the effects of solvents of various polarities on the electronic absorption and fluorescence spectra of RhB and Rh6G. The singlet‐state excited dipole moments (me) and ground state dipole moments (mg) were estimated from the equations of Bakshiev -Kawski and Chamma‐ Viallet using the variation of Stokes shift along with the solvent’s dielectric constant (e) and refractive indexes (n). The observed singlet‐state excited dipole moments were found to be larger than the ground‐state ones. Moreover, the obtained fluorescence quantum yield values were influenced by the environment of the fluorescing molecule. Consequently, the concentration of the dye solution, excited singlet state absorption and

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Publication Date
Fri Jan 01 2016
Journal Name
Engineering And Technology Journal
Face Retrieval Using Image Moments and Genetic Algorithm

Publication Date
Fri May 03 2024
Journal Name
Optical And Quantum Electronics
Design and analysis of a dual-core PCF biosensor based on SPR for cancerous cells detection

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