This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approache...
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This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter *** improvements were observed across various models,with SVM and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and *** study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among *** Trees and Random Forests exhibited stable performance throughout the *** enhancing accuracy,hyperparameter optimization also led to increased execution *** representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular *** research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.
Social network analysis (SNA) examines the social structures and relational patterns among entities, which are represented as nodes and edges within a network. It finds extensive application in various fields to deriv...
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Social network analysis (SNA) examines the social structures and relational patterns among entities, which are represented as nodes and edges within a network. It finds extensive application in various fields to derive insight into how these entities interact and exert influence on one another. Clustering refers to the tendency of nodes to form cohesive groups, whereby nodes within the same group exhibit higher levels of interconnection compared to those outside it. Understanding the flow of information through these clusters requires advanced methodologies to account for the intricacies and dynamics inherent in clusters, as their complexity often poses significant challenges. This research addresses the complexities associated with the exchange of information within clusters of real-world networks by analyzing the interactions among individual nodes and the pathways along which information is disseminated within these clusters. The article introduces the novel Awareness-Regulated-Spreading (ARS) model, an epidemic-based framework that elucidates how information propagates across networks by considering varying levels of transmissibility, ranging from localized sources to widespread dissemination within complex networks through activation probability. The experimental analysis reveals that the diffusion rate through a single edge is superior to that through triangular edges, and the activation probability surpasses that of state-of-the-art models such as the LACS and GACS models. As the probability of activation of clusters increases, the diffusion of information within these clusters also intensifies, although the clustering coefficient negatively impacts the diffusion process. In addition, the article explores the dynamics of information diffusion in the context of feedback loops and various edge characteristics. These advanced techniques offer deep insights into the flow of information, thereby facilitating more informed decision making in a highly connected worl
Internet of Vehicles(IoV)is an intelligent vehicular technology that allows vehicles to communicate with each other via *** and the Internet of Things(IoT)enable cutting-edge technologies including such self-driving *...
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Internet of Vehicles(IoV)is an intelligent vehicular technology that allows vehicles to communicate with each other via *** and the Internet of Things(IoT)enable cutting-edge technologies including such self-driving *** the existing systems,there is a maximum communication delay while transmitting the *** proposed system uses hybrid Cooperative,Vehicular Communication Management Framework called CAMINO(CA).Further it uses,energy efficient fast message routing protocol with Common Vulnerability Scoring System(CVSS)methodology for improving the communication delay,*** improves security while transmitting the messages through *** this research,we present a unique intelligent vehicular infrastructure communication management *** framework includes additional stability for both short and long-range mobile *** also includes built-in cooperative intelligent transport system(C-ITS)capabilities for experimental verification in real-world *** addition,an energy efficient-fast message distribution routing protocol(EE-FMDRP)has been *** combines the benefits between both temporal and direction oriented routing *** has been suggested for distributing information from the origin ends to the predetermined objective in a quick,accurate,and effective manner in the event of an *** critical value scale score(CVSS)employ ratings to measure the assault probability in Markov *** of chained transitions allow us to statistically evaluate the integrity of a group of *** the proposed method helps to enhance the vehicular *** CAMINO with energy efficient fast protocol using CVSS(CA-EEFP-CVSS)method outperforms in terms of shortest transmission latency achieves 2.6 sec,highest throughput 11.6%,and lowest energy usage 17%and PDR 95.78%.
Severe rainfall has seriously threatened human health and survival. Natural catastrophes such as floods, droughts, and many other natural disasters are caused by heavy rains, which people worldwide have to deal with t...
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Speech Emotion Recognition (SER) has seen much research done recently, but little is being done to minimize the effect of environmental noise on the predictions. Existing SER models primarily aim to learn the best fea...
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The paper presents a novel idea of proposing the application of Variational Autoencoders (VAEs) in crime detection for predicting face aging and deaging, which is one of the potential challenge of forensic science. VA...
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Recent advancements in computer science and engineering have significantly boosted interest in and success rate of speech recognition systems. Sophisticated speech recognition systems are being developed for a variety...
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Parkinson’s disease (PD) is a neurodegenerative disorder with slow progression whose symptoms can be identified at late stages. Early diagnosis and treatment of PD can help to relieve the symptoms and delay progressi...
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In this digital era,Cardio Vascular Disease(CVD)has become the lead-ing cause of death which has led to the mortality of 17.9 million lives each *** Diagnosis of the people who are at higher risk of CVDs helps them to...
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In this digital era,Cardio Vascular Disease(CVD)has become the lead-ing cause of death which has led to the mortality of 17.9 million lives each *** Diagnosis of the people who are at higher risk of CVDs helps them to receive proper treatment and helps prevent *** becomes inevitable to pro-pose a solution to predict the CVD with high accuracy.A system for predicting Cardio Vascular Disease using Deep Neural Network with Binarized Butterfly Optimization Algorithm(DNN–BBoA)is *** BBoA is incorporated to select the best *** optimal features are fed to the deep neural network classifier and it improves prediction accuracy and reduces the time *** usage of a deep neural network further helps to improve the prediction accu-racy with minimal *** proposed system is tested with two datasets namely the Heart disease dataset from UCI repository and CVD dataset from Kag-gle *** proposed work is compared with different machine learning classifiers such as Support Vector Machine,Random Forest,and Decision Tree Classifi*** accuracy of the proposed DNN–BBoA is 99.35%for the heart dis-ease data set from UCI repository yielding an accuracy of 80.98%for Kaggle repository for cardiovascular disease dataset.
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