Security and secure routing are important design issues in the design of Wireless Sensor Networks (WSNs). Intrusion Detection systems (IDSs) are useful for securing the communication in WSNs. An IDS can be developed b...
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One of the main goals of sentiment analysis is to analyze human perception to continuously adapt to each person’s demands. The information gathered is structured to understand the mood or emotional tone of the review...
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In healthcare,the persistent challenge of arrhythmias,a leading cause of global mortality,has sparked extensive research into the automation of detection using machine learning(ML)***,traditional ML and AutoML approac...
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In healthcare,the persistent challenge of arrhythmias,a leading cause of global mortality,has sparked extensive research into the automation of detection using machine learning(ML)***,traditional ML and AutoML approaches have revealed their limitations,notably regarding feature generalization and automation *** glaring research gap has motivated the development of AutoRhythmAI,an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of *** approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection,effectively bridging the gap between data preprocessing and model *** validate our system,we have rigorously tested AutoRhythmAI using a multimodal dataset,surpassing the accuracy achieved using a single dataset and underscoring the robustness of our *** the first pipeline,we employ signal filtering and ML algorithms for preprocessing,followed by data balancing and split for *** second pipeline is dedicated to feature extraction and classification,utilizing deep learning ***,we introduce the‘RRI-convoluted trans-former model’as a novel addition for binary-class *** ensemble-based approach then amalgamates all models,considering their respective weights,resulting in an optimal model *** our study,the VGGRes Model achieved impressive results in multi-class arrhythmia detection,with an accuracy of 97.39%and firm performance in precision(82.13%),recall(31.91%),and F1-score(82.61%).In the binary-class task,the proposed model achieved an outstanding accuracy of 96.60%.These results highlight the effectiveness of our approach in improving arrhythmia detection,with notably high accuracy and well-balanced performance metrics.
In the present research,we describe a computer-aided detection(CAD)method aimed at automatic fetal head circumference(HC)measurement in 2D ultrasonography pictures during all trimesters of *** HC might be utilized tow...
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In the present research,we describe a computer-aided detection(CAD)method aimed at automatic fetal head circumference(HC)measurement in 2D ultrasonography pictures during all trimesters of *** HC might be utilized toward determining gestational age and tracking fetal *** automated approach is particularly valuable in low-resource settings where access to trained sonographers is *** CAD system is divided into two steps:to begin,Haar-like characteristics were extracted from ultrasound pictures in order to train a classifier using random forests to find the fetal *** identified the HC using dynamic programming,an elliptical fit,and a Hough *** computer-aided detection(CAD)program was well-trained on 999 pictures(HC18 challenge data source),and then verified on 335 photos from all trimesters in an independent test set.A skilled sonographer and an expert in medicine personally marked the test *** used the crown-rump length(CRL)measurement to calculate the reference gestational age(GA).In the first,second,and third trimesters,the median difference between the standard GA and the GA calculated by the skilled sonographer stayed at 0.7±2.7,0.0±4.5,and 2.0±12.0 days,*** regular duration variance between the baseline GA and the health investigator’s GA remained 1.5±3.0,1.9±5.0,and 4.0±14 a couple of *** mean variance between the standard GA and the CAD system’s GA remained between 0.5 and 5.0,with an additional variation of 2.9 to 12.5 *** outcomes reveal that the computer-aided detection(CAD)program outperforms an expert *** paired with the classifications reported in the literature,the provided system achieves results that are comparable or even *** have assessed and scheduled this computerized approach for HC evaluation,which includes information from all trimesters of gestation.
Several newly developed techniques and tools for manipulating images, audio, and videos have been introduced as an outcome of the recent and rapid breakthroughs in AI, machine learning, and deep learning. While most a...
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Purpose:Generally,the scientific comparison has been done with the help of the overall impact of *** it is very easy to compare scholars,but how can we assess the scientific impact of scholars who have different resea...
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Purpose:Generally,the scientific comparison has been done with the help of the overall impact of *** it is very easy to compare scholars,but how can we assess the scientific impact of scholars who have different research careers?It is very obvious,the scholars may gain a high impact if they have more research experience or have spent more time(in terms of research career in a year).Then we cannot compare two scholars who have different research *** bibliometrics indicators address the time-span of *** this series,the h-index sequence and EM/EM’-index sequence have been introduced for assessment and comparison of the scientific impact of *** h-index sequence,EM-index sequence,and EM’-index sequence consider the yearly impact of scholars,and comparison is done by the index value along with their component *** time-series indicators fail to give a comparative analysis between senior and junior scholars if there is a huge difference in both scholars’research ***/methodology/approach:We have proposed the cumulative index calculation method to appraise the scientific impact of scholars till that age and tested it with 89 scholars ***:The proposed mechanism is implemented and tested on 89 scholars’publication data,providing a clear difference between the scientific impact of two *** also helps in predicting future prominent scholars based on their research *** limitations:This study adopts a simplistic approach by assigning equal credit to all authors,regardless of their individual ***,the potential impact of career breaks on research productivity is not taken into *** assumptions may limit the generalizability of our findings Practical implications:The proposed method can be used by respected institutions to compare their scholars *** agencies can also use it for similar ***/value:This research adds to the existing literature by
The Quantum Internet of Things (QIoT) in the healthcare industry holds the promise of transforming patient care, diagnostics, and medical research. Quantum-enhanced sensors, communication, and computation offer unprec...
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The Quantum Internet of Things (QIoT) in the healthcare industry holds the promise of transforming patient care, diagnostics, and medical research. Quantum-enhanced sensors, communication, and computation offer unprecedented capabilities that can revolutionize how healthcare services are delivered and experienced. This paper explores the potential of QIoT in the context of smart healthcare, where interconnected quantum-enabled devices and systems create an ecosystem that enhances data security, enables real-time monitoring, and advances medical knowledge. We delve into the applications of quantum sensors in precise health monitoring, the role of quantum communication in secure telemedicine, and the computational power of quantum computing in drug discovery and personalized medicine. We discuss challenges such as technical feasibility, scalability, and regulatory considerations, along with the emerging trends and opportunities in this transformative field. By examining the intersection of quantum technologies and smart healthcare, this paper aims to shed light on the novel approaches and breakthroughs that could redefine the future of healthcare delivery and patient outcomes. IEEE
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by challenges in social interaction, communication difficulties, repetitive behaviors, and a range of strengths and differences in...
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Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by challenges in social interaction, communication difficulties, repetitive behaviors, and a range of strengths and differences in cognitive abilities. Early ASD diagnosis using machine learning and deep learning techniques is crucial for preventing its severity and long-term effects. The articles published in this area have only applied different machine learning algorithms, and a notable gap observed is the absence of an in-depth analysis in terms of hyperparameter tuning and the type of dataset used in this context. This study investigated predictive modeling for ASD traits by leveraging two distinct datasets: (i) a raw CSV dataset with tabular data and (ii) an image dataset with facial expression. This study aims to conduct an in-depth analysis of ASD trait prediction in adults and toddlers by doing hyper optimized and interpreting the result through explainable AI. In the CSV dataset, a comprehensive exploration of machine learning and deep learning algorithms, including decision trees, Naive Bayes, random forests, support vector machines (SVM), k-nearest neighbors (KNN), logistic regression, XGBoost, and ANN, was conducted. XGBoost emerged as the most effective machine learning algorithm, achieving an accuracy of 96.13%. The deep learning ANN model outperformed the traditional machine learning algorithms with an accuracy of 99%. Additionally, an ensemble model combining a decision tree, random forest, SVM, KNN, and logistic regression demonstrated superior performance, yielding an accuracy of 96.67%. The XGBoost model, utilized in hyperparameter optimization for CSV data, exhibited a substantial accuracy increase, reaching 98%. For the image dataset, advanced deep learning models, such as ResNet50, VGG16, Boosting, and Bagging, were employed. The bagging model outperformed the others, achieving an impressive accuracy of 99%. Subsequent hyperparameter optimization was conduct
The extensive spread of DeepFake images on the internet has emerged as a significant challenge, with applications ranging from harmless entertainment to harmful acts like blackmail, misinformation, and spreading false...
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Understanding and predicting air quality is pivotal for public health and environmental management, especially in urban areas like Delhi. This study utilizes a comprehensive dataset from the Central Pollution Control ...
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