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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
Mon Dec 01 2025
Journal Name
International Communications In Heat And Mass Transfer
Design optimization and performance analysis of a PCM-to-air heat exchanger with optimized fin configuration for building heating applications
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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Applying some hybrid models for modeling bivariate time series assuming different distributions for random error with a practical application
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Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Training Program Based on Employing the Educational Portal in Developing the Skills of the Administrative Body in Basic Education Schools in Dhofar Governorate
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The objective of the study was to identify the effectiveness of a training program based on the employment of the educational portal in the development of the skills of the administrative body in the basic education schools in Dhofar Governorate. To achieve the goal, a training program was designed that includes the skills of the educational portal to be met by the administrative body and measuring its effectiveness. A questionnaire to identify training needs, and a notecard to evaluate performance. The study sample consisted of (70) individuals of the administrative staff. The researchers used the descriptive-analytical method to identify the training needs, design and build the training program and the experimental method for applying

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Publication Date
Wed Dec 20 2017
Journal Name
Anglisticum.
The Pragmatic Argumentation of Discourse Markers in English Academic Writing: A Corpus-Based Analysis الحجة التداولية لعلامات الخطاب في الكتابة الأكاديمية الإنكليزية: تحليل يعتمد على البيانات المحوسبة
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Academic writing is a key skill for success in academic life, particularly for graduate students of a foreign language. The importance of writing to academic culture, practice, and knowledge building has led to a great deal of research in many fields, including rhetoric and composition, linguistics, applied linguistics, and English for Academic Purposes (EAP). Often, studies and research investigating academic writing are motivated by the need to inform the learning of writing to native and non-native English-speaking students, through both descriptions of professional academic writing as well as through comparisons of novice writer (native and non-native Englishspeaking) and expert production. However, while learning about academic writing

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Publication Date
Wed Oct 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Degree of Student Teachers Acquisition at Sultan Qaboos University in Skills of Teaching Arabic via A Virtual Micro-Teaching Lab Based on their Point of View
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The study aims to investigate the degree of student teachers at Sultan Qaboos University acquired skills in teaching Arabic via a virtual micro-teaching lab, as well as to reveal the difficulties they faced and their development proposals. To do this, the researchers developed a questionnaire divided into four dimensions: planning, implementation, evaluation, and

ethical values for the teaching profession, in addition to two open-ended questions to identify difficulties and suggestions. It was administered to (30) student teachers. The results revealed that the average degree of student-teacher acquisition of skills was high in its four dimensions. It ranged between (39.2) to (82.2), while the overall average was (56.2).

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Recording of an ECG, PCG, and PPG for Feature Extractions
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Recently, the development of the field of biomedical engineering has led to a renewed interest in detection of several events. In this paper a new approach used to detect specific parameter and relations between three biomedical signals that used in clinical diagnosis. These include the phonocardiography (PCG), electrocardiography (ECG) and photoplethysmography (PPG) or sometimes it called the carotid pulse related to the position of electrode.

Comparisons between three cases (two normal cases and one abnormal case) are used to indicate the delay that may occurred due to the deficiency of the cardiac muscle or valve in an abnormal case.

The results shown that S1 and S2, first and second sound of the

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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Engineering And Applied Sciences
Feasibility Study of Applying a Pattern Waterflood Without and with Peripheral Injectors for Maximizing Oil Recovery Under Limited Water Sources Availability A Case Study of Heterogeneous Giant Carbonate Reservoir
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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
An Application Domain Based on General Object Oriented Software Models
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Any software application can be divided into four distinct interconnected domains namely, problem domain, usage domain, development domain and system domain. A methodology for assistive technology software development is presented here that seeks to provide a framework for requirements elicitation studies together with their subsequent mapping implementing use-case driven object-oriented analysis for component based software architectures. Early feedback on user interface components effectiveness is adopted through process usability evaluation. A model is suggested that consists of the three environments; problem, conceptual, and representational environments or worlds. This model aims to emphasize on the relationship between the objects

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Publication Date
Mon Sep 21 2020
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
Emotion Recognition Based on Mining Sub-Graphs of Facial Components
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Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Nanoelectronics And Optoelectronics
Hypothetical Design of Carbon Nanotube Materials Based on [8]Circulene
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B3LYP/6-31G, DFT method was applied to hypothetical study the design of six carbon nanotube materials based on [8]circulene, through the use of cyclic polymerization of two and three molecules of [8]circulene. Optimized structures of [8]circulene have saddle-shaped. Design of six carbon nanotubes reactions were done by thermodynamically calculating (Δ S, Δ G and Δ H) and the stability of these hypothetical nanotubes depending on the value of HOMO energy level. Nanotubes obtained have the most efficient gap energy, making them potentially useful for solar cell applications.