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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 medical images with favorable results. It can help save lives faster and rectify some medical errors. In this study, we look at the most up-to-date methodologies for medical image analytics that use convolutional neural networks on MRI images. There are several approaches to diagnosing and classifying brain cancers. Inside the brain, irregular cells grow so that a brain tumor appears. The size of the tumor and the part of the brain affected impact the symptoms.

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Publication Date
Sat Jan 01 2022
Journal Name
Intelligent Automation & Soft Computing
A Novel Classification Method with Cubic Spline Interpolation
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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Engineering
A Comprehensive Review for Integrating Petrophysical Properties, Rock Typing, and Geological Modeling for Enhanced Reservoir Characterization
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Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Data Analytics and Blockchain: A Review
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Blockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships between data points to draw meaningful conclusions. The field of data analytics in Blockchain is relatively new, and few studies have been conducted to examine the challenges involved in Blockchain data analytics. This article presents a systematic analysis of how data analytics affects Blockchain performance, with the aim of investigating the current state of Blockchain-based data analytics techniques in research fields and

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Publication Date
Fri Nov 18 2022
Journal Name
International Journal Of Nanoscience
Plasma Production and Applications: A Review
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Large amounts of plasma, the universe’s fourth most common kind of stuff, may be found across our galaxy and other galaxies. There are four types of matter in the cosmos, and plasma is the most common. By heating the compressed air or inert gases to create negatively and positively charged particles known as ions, electrically neutral particles in their natural state are formed. Many scientists are currently focusing their efforts on the development of artificial plasma and the possible advantages it may have for humankind in the near future. In the literature, there is a scarcity of information regarding plasma applications. It’s the goal of this page to describe particular methods for creating and using plasma, which may be us

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Image And Graphics
DAB-UNET: Dual Attention Block UNET Segmentation for Diabetic Retinopathy Utilizing an Encoder-Decoder Residual
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—Fundus images play an essential role in ophthalmic diagnostics for the detection of many eye illnesses. The experiment begins with a thorough image preprocessing. technique, which includes clipping the circular borders, scaling the image, enhancing the contrast, removing noise, and augmenting the data. The new combined block applies to extracting distinctive deep feature representations, which help to detect the first shape of the edges of each lesion. It is namely the Attention Block and the Conv-Deconv UNET model. The attention block is subsequently implemented in order to augment the robustness and quality of feature depictions derived from a pair of DR images. The Dual Attention Block for the backbone, which is supplement

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Publication Date
Mon Jul 27 2026
Journal Name
Journal Of Baghdad College Of Dentistry
A Comparative Immunohistochemical Expression of Cyclin D1 in Keratocystic Odontogenic Tumor, Dentigerous and Radicular Cysts
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Background: Odontogenic cysts include a group of osseodestructive lesions that frequently affect the jaws. Those cysts could derive from odontogenic epithelium and occur in the tooth-bearing regions of the jaws. The aims of this study were to evaluate the immunohistochemical expression of Cyclin D1 in Keratocystic Odontogenic Tumor, Dentigerous cyst and Radicular cyst in epithelium and connective tissue capsule. Materials and Methods: In this study, thirty formalin fixed paraffin embedded tissue blocks of Odontogenic cysts and Tumor, consist of 14 Keratocystic Odontogenic Tumor, 8 dentigerous cysts and 8 radicular cysts were analyzed immunohistochemically for the presence of Cyclin D1 proteins. Results: Strong to moderate expression of Cy

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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Dyslipidemia and CA15-3 serum level in Iraqi Women with Breast Tumor: A Comparative Study
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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
mathematical model for segmentation of the overall planning of puplic redemption company- ministry of industry and minerals
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Abstract

The study presents a mathematical model with a disaggregating approach to the problem of production planning of a fida Company; which belongs to the ministry of Industry. The study considers disaggregating the entire production into 3 productive families of (hydraulic cylinders, Aldblatt (dampers), connections hydraulics with each holds similar characteristics in terms of the installation cost, production time and stock cost. The Consequences are an ultimate use of the available production capacity as well as meeting the requirements of these families at a minimal cost using linear programming. Moreover, the study considers developing a Master production schedule that drives detailed material and production requi

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Publication Date
Mon Aug 03 2020
Journal Name
Rawal Medical Journal
Functional outcomes of sandwich reconstruction technique for giant cell tumor around the knee joint
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Objective: To evaluate the functional outcomes after extended curettage and reconstruction using a combination of bone graft and bone cement (sandwich). Methodology: In this prospective case series 16 skeletally mature patients with primary giant cell tumor around the knee were included. Patients with previous surgically treated, malignant transformation, degenerative knee changes and those presenting with pathological fracture were excluded. The tumor was excised with bone graft filling space beneath the articular cartilage and a block of gel foam was placed over the cortical surface of picked bone graft. Remaining cavity was filled with polymethylmethacrylate cement (sandwich) with or without internal fixation. The func tional evaluation

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Publication Date
Fri Nov 01 2013
Journal Name
Radioelectronics And Communications Systems
Erratum to: “BER Performance Enhancement for Secure Wireless Communication Systems Based on DCSK-MIMO Techniques under Rayleigh Fading Channel”
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There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide low bit error rates (BER) along with information security. The aim of such activity is to steal or distort the information being conveyed. Optical Wireless Systems (basically Free Space Optic Systems, FSO) are no exception to this trend. Thus, there is an urgent necessity to design techniques that can secure privileged information against unauthorized eavesdroppers while simultaneously protecting information against channel-induced perturbations and errors. Conventional cryptographic techniques are not designed

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