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A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesion from five Macaca fasicularis monkeys. The proposed classifier is based on a CNN using filtered segmented EMG signals from the pre- and post-lesion periods as inputs, while the kNN is designed using four hand-crafted EMG features. The results suggest that the CNN provides a promising classification technique for TSCI, compared to conventional machine learning classification. The kNN with hand-crafted EMG features classified the pre- and post-lesion EMG data with an F-measure of 89.7% and 92.7% for the left- and right-side muscles, respectively, while the CNN with the EMG segments classified the data with an F-measure of 89.8% and 96.9% for the left- and right-side muscles, respectively. Finally, the proposed deep learning classification model (CNN), with its learning ability of high-level features using EMG segments as inputs, shows high potential and promising results for use as a TSCI classification system. Future studies can confirm this finding by considering more subjects.

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Satellite image classification using proposed singular value decomposition method
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In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

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Publication Date
Sun Dec 02 2018
Journal Name
Journal Of The College Of Education For Women
Features of (Possible for Itself) in the (Alashaira) opinion – Spoken Study
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My study here is about the (possible for itself) features especially in the (Alashaira) opinion, also I touch to the other logicians opinions, I clarified these features concisely in the preface to be clear in front of the reader, I made it in two studies and five subjects.I talked about the meaning of the existence in the ((possible for itself) theme, and I clarified its types in the logicians and the philosophers' opinions, through which the existence and the nonexistence are equal in it, as it cannot be existed nor be nonsexist unless with a separated reason, and there is no necessity to oblige its existence, or its nonexistence is impossible.Then I talked about the outweighing of the (possible for itself) as one side  of the exi

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Publication Date
Wed Sep 15 2021
Journal Name
Al-academy
Design features of medicine box packaging for children: منى محمود حسين
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Graphic design constitutes the human necessity for the design action, so there is no design achievement that is not considered in its founding project and its final realization as a response to a specific necessity. As a result of knowledge, which is the product of experience and is the result of applied science, design is based on observation, study and development, leading to the main goal, which is the utilitarian and aesthetic function that is put into the final consideration of design, and drug packaging design has an important role in all marketing fields, as companies compete with each other to attract the largest number Possible from consumers in a way that guarantees them material profit, and in order to achieve this, it always

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Publication Date
Thu Jun 27 2024
Journal Name
Journal Of Image And Graphics
ALL-FABNET: Acute Lymphocytic Leukemia Segmentation Using a Flipping Attention Block Decoder-Encoder Network
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Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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Publication Date
Thu Dec 09 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Thymoquinone Attenuates Immune Mediated Liver Injury Induced by Concanavalin A in Mice
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Autoimmune hepatitis is an inflammatory disease and its incidence has been increasing. The features of hepatitis are the release of inflammatory cytokines, the elevation of AST and ALT, and hepatocyte apoptosis and necrosis. Concanavalin A considered as essential model represents the acute immune-mediated liver damage in rodents. Thymoquinone is well known herbal compound that exert hepatoprotective, anti-inflammatory, and antioxidant activity. In this study, we focus on the immunoregulatory and liver protective effect of thymoquinone in a mouse model of concanavalin A-induced liver injury.

Twenty-four male mice were randomly divided into four groups each containing six animals: Negative control group, concanavalin A model group,

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Publication Date
Sun Oct 05 2025
Journal Name
Mesopotamian Journal Of Computer Science
DGEN: A Dynamic Generative Encryption Network for Adaptive and Secure Image Processing
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Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix

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Publication Date
Fri Aug 19 2022
Journal Name
Mathematical Statistician And Engineering Applications (msea)
Application of TOPSIS method for Multi-Criteria Decision Making for poultry fields By using GIS in Hilla district
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Statistical methods and statistical decisions making were used to arrange and analyze the primary data to get norms which are used with Geographic Information Systems (GIS) and spatial analysis programs to identify the animals production and poultry units in strategic nutrition channels, also the priorities of food insecurity through the local production and import when there is no capacity for production. The poultry production is one of the most important commodities that satisfy human body protein requirements, also the most important criteria to measure the development and prosperity of nations. The poultry fields of Babylon Governorate are located in Abi Ghareg and Al_Kifil centers according to many criteria or factors such as the popu

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Publication Date
Thu Sep 01 2016
Journal Name
Physica Medica
Quantitative analysis of sentinel lymph node detection using a novel small field of view hybrid gamma camera (HGC)
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Introduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm

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Publication Date
Sun Feb 17 2019
Journal Name
Iraqi Journal Of Physics
Classification of the galaxy Milky Way using variable precision rough sets technique
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Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

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