Gliomas are aggressive brain tumors known for their heterogeneity,unclear borders,and diverse locations on Magnetic Resonance Imaging(MRI)*** factors present significant challenges for MRI-based segmentation,a crucial...
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Gliomas are aggressive brain tumors known for their heterogeneity,unclear borders,and diverse locations on Magnetic Resonance Imaging(MRI)*** factors present significant challenges for MRI-based segmentation,a crucial step for effective treatment planning and monitoring of glioma *** study proposes a novel deep learning framework,ResNet Multi-Head Attention U-Net(ResMHA-Net),to address these challenges and enhance glioma segmentation ***-Net leverages the strengths of both residual blocks from the ResNet architecture and multi-head attention *** powerful combination empowers the network to prioritize informative regions within the 3D MRI data and capture long-range *** doing so,ResMHANet effectively segments intricate glioma sub-regions and reduces the impact of uncertain tumor *** rigorously trained and validated ResMHA-Net on the BraTS 2018,2019,2020 and 2021 ***,ResMHA-Net achieved superior segmentation accuracy on the BraTS 2021 dataset compared to the previous years,demonstrating its remarkable adaptability and robustness across diverse ***,we collected the predicted masks obtained from three datasets to enhance survival prediction,effectively augmenting the dataset *** features were then extracted from these predicted masks and,along with clinical data,were used to train a novel ensemble learning-based machine learning model for survival *** model employs a voting mechanism aggregating predictions from multiple models,leading to significant improvements over existing *** ensemble approach capitalizes on the strengths of various models,resulting in more accurate and reliable predictions for patient ***,we achieved an impressive accuracy of 73%for overall survival(OS)prediction.
This study aims to revolutionize predictive maintenance in semiconductor manufacturing by using the SECOM dataset. The main objective is to create a precise and flexible predictive model by combining the XGBoost algor...
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Yoga practice offers numerous health benefits, but incorrect poses can lead to injuries and hinder progress. This project leverages the power of deep learning, specifically Convolutional Neural Networks (CNNs) and Ten...
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This research work explores the effects of dry, liquid N2-based cryogenic cooling and cryogenic plus MQL hybrid strategy on surface roughness, rake surface temperature, principal cutting-edge temperature, auxiliary cu...
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RagaMoodSync presents an innovative framework for personalized music therapy through Hindustani Raga recommendations based on facial emotion recognition. Utilizing a Fusion-DenseNet (FusDenseNet) architecture with adv...
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In this work, we present milliGait, a user identification using gait patterns captured by millimeter wave (mmWave) radar technology. milliGait takes into account the unique movement signatures of individuals to enable...
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The hand localization problem has been a longstanding focus due to its many applications. The task involves modeling the hand as a singular point and determining its position within a defined coordinate system. Howeve...
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This project addresses the global health challenge posed by glaucoma through the development of an innovative Python-based application. Utilizing advanced machine learning techniques, specifically the VGG16 model with...
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The Vertical Handover(VHO)is one of the most vital features provided for the heterogeneous mobile *** allows Mobile Users(MUs)to keep ongoing sessions without disruption while they continuously move between different ...
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The Vertical Handover(VHO)is one of the most vital features provided for the heterogeneous mobile *** allows Mobile Users(MUs)to keep ongoing sessions without disruption while they continuously move between different Radio Access Technologies(RATs)such as Wireless Fidelity(Wi-Fi),Global System for Mobile Communication(GSM),Universal Mobile Telecommunications System(UMTS),Long Term Evolution(LTE)and Fifth Generation(5G).In order to fulfill this goal,the VHO must comply to three main phases:starting of collecting the required information and then passing it for decision phase to obtain the best available RAT for performing VHO by execution phase ***,the execution phase still encounters some security issues which are exploited by hackers in launching malicious attacks such as ransomware,fragmentation,header manipulation,smurf,host initialization,reconnaissance,eavesdropping,Denial of Service(DoS),spoofing,Man in the Middle(MITM)and *** paper thoroughly studies the recent security issues for hundreds VHO approaches found in the literature and comes up with a secure procedure to enhance VHO security during execution phase.A numerical analysis results of the proposed procedure are effectively evaluated in terms of security and signaling *** with the recent related work found in literature,the analysis demonstrates that the security is successfully improved by 20%whereas signaling cost is maintained as in non-proposed procedure.
This research proposes an innovative method for categorizing phishing and legitimate websites based on content features extracted from their HTML structure. Leveraging data collection with the requests library and HTM...
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