Cryptocurrencies like Bitcoin and Ethereum use the blockchain technology, that is known for providing significant security advantages. But there is more to Bitcoin and Ethereum than that. They use digital signatures t...
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Seizures that take place repeatedly and without provocation are referred to as epilepsy. Epilepsy can be diagnosed with electroencephalography (EEG). One of the most influential challenges of the past few years has be...
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Security is a primary concern in communication for reliable transfer ofinformation between the authenticated members, which becomes more complexin a network of Internet of Things (IoT). To provide security for group c...
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Security is a primary concern in communication for reliable transfer ofinformation between the authenticated members, which becomes more complexin a network of Internet of Things (IoT). To provide security for group communication a key management scheme incorporating Bilinear pairing technique withMulticast and Unicast key management protocol (BMU-IOT) for decentralizednetworks has been proposed. The first part of the proposed work is to dividethe network into clusters where sensors are connected to and is administered bycluster head. Each sensor securely shares its secret keys with the cluster headusing unicast. Based on these decryption keys, the cluster head generates a common encryption key using bilinear pairing. Any sensor in the subgroup candecrypt the message, which is encrypted by the common encryption key. Theremaining part focuses to reduce communication, computation and storage costsof the proposed framework and the resilience against various attacks. The implementation is carried out and results are compared with the existing schemes thathave given considerably better results. Thus, the lightweight devices of IoT canprovide efficiency and security by reducing their overhead in terms of complexity.
Handling sentiment drifts in real time twitter data streams are a challen-ging task while performing sentiment classifications,because of the changes that occur in the sentiments of twitter users,with respect to *** g...
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Handling sentiment drifts in real time twitter data streams are a challen-ging task while performing sentiment classifications,because of the changes that occur in the sentiments of twitter users,with respect to *** growing volume of tweets with sentiment drifts has led to the need for devising an adaptive approach to detect and handle this drift in real *** work proposes an adap-tive learning algorithm-based framework,Twitter Sentiment Drift Analysis-Bidir-ectional Encoder Representations from Transformers(TSDA-BERT),which introduces a sentiment drift measure to detect drifts and a domain impact score to adaptively retrain the classification model with domain relevant data in real *** framework also works on static data by converting them to data streams using the Kafka *** experiments conducted on real time and simulated tweets of sports,health care andfinancial topics show that the proposed system is able to detect sentiment drifts and maintain the performance of the classification model,with accuracies of 91%,87%and 90%,*** the results have been provided only for a few topics,as a proof of concept,this framework can be applied to detect sentiment drifts and perform sentiment classification on real time data streams of any topic.
Heart attack is a catch-all term for a variety of conditions affecting the heart. Analysis of large amounts of data and comparisons between them are essential for the prediction, prevention, and management of cardiova...
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This work studies the performance of the pretrained models to classify colorectal tissues and the effectiveness of tissue image classification models when it is applied across different datasets that may exhibit diffe...
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In the proposed model, a novel approach is introduced to discover an optimal machine learning model for food demand prediction. To create an exemplary model, we used twelve different machine learning models to analyse...
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作者：
Ratanavilisagul, Chiabwoot
Faculty of Applied Science Department of Computer and Information Science Bangkok Thailand
multi-skills resource-constrained project scheduling problem (MS-RCPSP) is assigned to employees under the predecessor tasks constraint and the multi-skills constraint in order to create the feasible schedule with bot...
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This research employs Convolutional Neural Networks (CNNs) to distinguish between ripe and spoiled fruits using deep learning. The CNN model achieves an impressive accuracy rate of 98.79% in accurately categorizing th...
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All the known Group Decision Making (GDM) models assume the continuous availability of all decision-makers (DMs) during the Consensus Reaching Process (CRP). Factually, the constant presence of a DM means that the con...
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