We propose a fair distributed computing platform based on Distributed Ledger technology (DLT) and performance measurements. The platform integrates DLT and federated learning, enabling users to train machine learning ...
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Big Data applications face different types of complexities in *** and purifying data by eliminating irrelevant or redundant data for big data applications becomes a complex operation while attempting to maintain discr...
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Big Data applications face different types of complexities in *** and purifying data by eliminating irrelevant or redundant data for big data applications becomes a complex operation while attempting to maintain discriminative features in processed *** existing scheme has many disadvantages including continuity in training,more samples and training time in feature selections and increased classification execution *** ensemble methods have made a mark in classification tasks as combine multiple results into a single *** comparing to a single model,this technique offers for improved *** based feature selections parallel multiple expert’s judgments on a single *** major goal of this research is to suggest HEFSM(Heterogeneous Ensemble Feature Selection Model),a hybrid approach that combines multiple *** major goal of this research is to suggest HEFSM(Heterogeneous Ensemble Feature Selection Model),a hybrid approach that combines multiple ***,individual outputs produced by methods producing subsets of features or rankings or voting are also combined in this ***(K-Nearest Neighbor)classifier is used to classify the big dataset obtained from the ensemble learning *** results found of the study have been good,proving the proposed model’s efficiency in classifications in terms of the performance metrics like precision,recall,F-measure and accuracy used.
Sequence-to-sequence models are fundamental building blocks for generating abstractive text summaries, which can produce precise and coherent summaries. Recently proposed, different text summarization models aimed to ...
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Background: Epilepsy is a neurological disorder that leads to seizures. This occurs due to excessive electrical discharge by the brain cells. An effective seizure prediction model can aid in improving the lifestyle of...
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Deep neural networks have succeeded in learning balanced and imbalanced data in the field of pneumonia diagnosis. However, both require separate model designs in their respective domains. The pneumonia recognition met...
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The incorporation of Machine Learning (ML) and Artificial Intelligence (AI) technologies across diverse industries presents considerable potential for both economic expansion and societal ***, which includes both Narr...
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In today's recommendation systems, people's ratings of products are important criteria for analysis. For instance, a recommendation system based on content analysis may be utilized. However, this can lead to a...
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This technical abstract makes a specialty of an Iota-based strategy to enhance the performance of livestock monitoring and management. The proposed answer involves the usage of wireless sensors and mobile gadgets to g...
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Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) ...
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Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.
Blockchain is one of the emerging technologies that are applied in various fields and its application in Healthcare 4.0 is crucial to handle the vast amount of health records that are growing continuously everyday. Th...
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