This paper presents a coding approach for achieving omnidirectional transmission of certain common signals in massive multi-input multi-output (MIMO) networks such that the received power at any direction in a cell re...
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A secure framework for storing EHR in the hybrid cloud platform is implemented. At first, the required medical data is gathered from the database of the hospitals and split into sensitive and insensitive parts. The se...
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Autism spectrum disorder(ASD)can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics,like changes in behavior,social disabilities,and difficulty communi...
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Autism spectrum disorder(ASD)can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics,like changes in behavior,social disabilities,and difficulty communicating with *** tracking(ET)has become a useful method to detect *** vital aspect of moral erudition is the aptitude to have common visual *** eye-tracking approach offers valuable data regarding the visual behavior of children for accurate and early ***-tracking data can offer insightful information about the behavior and thought processes of people with ASD,but it is important to be aware of its limitations and to combine it with other types of data and assessment techniques to increase the precision of ASD *** operates by scanning the paths of eyes for extracting a series of eye projection points on images for examining the behavior of children with *** purpose of this research is to use deep learning to identify autistic disorders based on eye *** Chaotic Butterfly Optimization technique is used to identify this specific ***,this study develops an ET-based Autism Spectrum Disorder Diagnosis using Chaotic Butterfly Optimization with Deep Learning(ETASD-CBODL)*** presented ETASDCBODL technique mainly focuses on the recognition of ASD via the ET and DL *** accomplish this,the ETASD-CBODL technique exploits the U-Net segmentation technique to recognize interested *** addition,the ETASD-CBODL technique employs Inception v3 feature extraction with CBO algorithm-based hyperparameter ***,the long-shorttermmemory(LSTM)model is exploited for the recognition and classification of *** assess the performance of the ETASD-CBODL technique,a series of simulations were performed on datasets from the figure-shared data *** experimental values of accuracy(99.29%),precision(98.78%),sensitivity(99.29%)and specificity(99.29%)showed a better perfo
Handwritten text recognition software is used to recognize and extract text from scanned documents. The fun-damental goal of this technology is to transform printed or handwritten text into an easily readable electron...
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Understanding the learner’s requirements and status is important for recommending relevant and appropriate learning materials to the learner in personalized learning. For this purpose, the learning recommendatio...
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The convolution layer in a convolutional neural network (CNN) is highly computationally intensive. It is crucial to design reusable low-cost hardware IP for convolutional layer for enabling hardware-based feature extr...
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Diabetic Eye Disease(DED)is a fundamental cause of blindness in human beings in the medical *** techniques are proposed to forecast and examine the stages in Prognostication of Diabetic Retinopathy(DR).The Machine Lea...
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Diabetic Eye Disease(DED)is a fundamental cause of blindness in human beings in the medical *** techniques are proposed to forecast and examine the stages in Prognostication of Diabetic Retinopathy(DR).The Machine Learning(ML)and the Deep Learning(DL)algorithms are the predomi-nant techniques to project and explore the images of *** though some solu-tions were adapted to challenge the cause of DR disease,still there should be an efficient and accurate DR prediction to be adapted to refine its *** this work,a hybrid technique was proposed for classification and prediction of *** proposed hybrid technique consists of Ensemble Learning(EL),2 Dimensional-Conventional Neural Network(2D-CNN),Transfer Learning(TL)and Correlation ***,the Stochastic Gradient Boosting(SGB)EL method was used to predict the ***,the boosting based EL method was used to predict the DR of *** 2D-CNN was applied to categorize the various stages of DR ***,the TL was adopted to transfer the clas-sification prediction to training *** this TL was applied,a new predic-tion feature was *** the experiment,the proposed technique has achieved 97.8%of accuracy in prophecies of DR images and 98%accuracy in grading of *** experiment was also extended to measure the sensitivity(99.6%)and specificity(97.3%)*** predicted accuracy rate was com-pared with existing methods.
Every day,websites and personal archives create more and more *** size of these archives is *** comfort of use of these huge digital image gatherings donates to their ***,not all of these folders deliver relevant inde...
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Every day,websites and personal archives create more and more *** size of these archives is *** comfort of use of these huge digital image gatherings donates to their ***,not all of these folders deliver relevant indexing *** the outcomes,it is dif-ficult to discover data that the user can be absorbed ***,in order to determine the significance of the data,it is important to identify the contents in an informative *** annotation can be one of the greatest problematic domains in multimedia research and computer ***,in this paper,Adap-tive Convolutional Deep Learning Model(ACDLM)is developed for automatic image ***,the databases are collected from the open-source system which consists of some labelled images(for training phase)and some unlabeled images{Corel 5 K,MSRC v2}.After that,the images are sent to the pre-processing step such as colour space quantization and texture color class *** pre-processed images are sent to the segmentation approach for efficient labelling technique using J-image segmentation(JSEG).Thefinal step is an auto-matic annotation using ACDLM which is a combination of Convolutional Neural Network(CNN)and Honey Badger Algorithm(HBA).Based on the proposed classifier,the unlabeled images are *** proposed methodology is imple-mented in MATLAB and performance is evaluated by performance metrics such as accuracy,precision,recall and F1_*** the assistance of the pro-posed methodology,the unlabeled images are labelled.
This document thoroughly explores the Elastic Stack, comprising Elasticsearch, Logstash, Kibana, and Beats, emphasizing its effectiveness in real-time data analysis, log handling, and visualization. It examines the es...
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The highly infectious and mutating COVID-19, known as the novel coronavirus, poses a substantial threat to both human health and the global economy. Detecting COVID-19 early presents a challenge due to its resemblance...
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