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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
Thu Oct 01 2015
Journal Name
Engineering And Technology Journal
Genetic Based Optimization Models for Enhancing Multi- Document Text Summarization
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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Arduino-Based Controller for Sequence Development of Automated Manufacturing System
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It has become necessary to change from a traditional system to an automated system in production processes, because it has high advantages. The most important of them is improving and increasing production. But there is still a need to improve and develop the work of these systems. The objective of this work is to study time reduction by combining multiple sequences of operations into one process. To carry out this work, the pneumatic system is designed to decrease\ increase the time of the sequence that performs a pick and place process through optimizing the sequences based on the obstacle dimensions. Three axes are represented using pneumatic cylinders that move according to the sequence used. The system is implemented and

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Publication Date
Thu Dec 01 2022
Journal Name
Neuroscience Informatics
Epileptic EEG activity detection for children using entropy-based biomarkers
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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Application Or Innovation In Engineering & Management (ijaiem)
Probabilistic Neural Network for User Authentication Based on Keystroke Dynamics
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Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Matching Algorithms for Intrusion Detection System based on DNA Encoding
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Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

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Publication Date
Tue Sep 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Arduino-Based Controller for Sequence Development of Automated Manufacturing System
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It has become necessary to change from a traditional system to an automated system in production processes, because it has high advantages. The most important of them is improving and increasing production. But there is still a need to improve and develop the work of these systems.

The objective of this work is to study time reduction by combining multiple sequences of operations into one process. To carry out this work, the pneumatic system is designed to decrease\ increase the time of the sequence that performs a pick and place process through optimizing the sequences based on the obstacle dimensions. Three axes are represented using pneumatic cylinders that move according to the sequence used. The system is implemented and con

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Publication Date
Fri Jul 12 2024
Journal Name
Aaps Pharmscitech
Nanosuspension-Based Repaglinide Fast-Dissolving Buccal Film for Dissolution Enhancement
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Drug solubility and dissolution remain a significant challenge in pharmaceutical formulations. This study aimed to formulate and evaluate repanglinide (RPG) nanosuspension-based buccal fast-dissolving films (BDFs) for dissolution enhancement. RPG nanosuspension was prepared by the antisolvent-precipitation method using multiple hydrophilic polymers, including soluplus®, polyvinyl alcohol, polyvinyl pyrrolidine, poloxamers, and hydroxyl propyl methyl cellulose. The nanosuspension was then directly loaded into BDFs using the solvent casting technique. Twelve formulas were prepared with a particle size range of 81.6-1389 nm and PDI 0.002-1 for the different polymers. Nanosuspensions prepared with soluplus showed a favored mean particle size o

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Publication Date
Sat Jul 09 2022
Journal Name
Wireless Communications And Mobile Computing
An Optimized Approach for Industrial IoT Based on Edge Computing
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The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

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Publication Date
Fri Sep 27 2019
Journal Name
Journal Of Baghdad College Of Dentistry
The Impact of Chronic Periodontitis on Mother-Infant Bonding Status in Relation to Salivary Tumor Necrosis Factor Alpha and Interleukin-6
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Background: Chronic periodontitis is a bacterial infection that result in bone destruction associated with the increasing level of salivary tumor necrosis alpha and interleukin6 that affect Mother-infant bonding status. The aim of the present study was to assess the relationship between the Mother-infant bonding status in mothers with chronic periodontitis in relation to Salivary Tumor necrosis factor alpha and Salivary Interleukin6. Materials and Methods: The selected sample consisted of mothers with chronic periodontitis compared with mothers with healthy periodontium in postpartum period, their age ranged between 30-40 years. Both groups were subjected to postpartum Bonding Questionnaire (PBQ). Periodontal health status was assessed f

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Publication Date
Wed Feb 15 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Instructional Design According to the Repulsive Learning Model and its Impact on the Achievement of Chemistry and Lateral Thinking for Third-Grade Intermediate Students
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Identify the effect of an educational design according to the repulsive (allosteric) learning model on the achievement of chemistry and lateral thinking. The sample consisted of (59) students from third-grade intermediate students. They were randomly distributed into two groups (experimental and control), and the equivalence was done in (chronological age, previous achievement in chemistry, intelligence, lateral thinking). The (30) students from experimental group were taught according to the instructional design, other 29 students from the (control) group were taught according to the usual method. Two tests done, one of them is an achievement test consisted of (30) items of the type of multiple choice, the other was a lateral think

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