Water loss from fruit and vegetable production is mostly caused by leakage in the transportation system and handling of land, as well as by using traditional processing techniques. In order to increase the wellness of...
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In today's digital era, the Internet holds a fundamental position in daily life, particularly in Sri Lanka. This study addresses two primary objectives: first, to quantify the technical performance of internet ser...
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This review investigates the effectiveness of exploiting the massive Artificial Intelligence (AI) technology in the diagnosis of prostate cancer histopathological images. It focuses on studying and analyzing the curre...
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The rapid advancement of technology has undoubtedly brought comfort to humanity, but it also necessitates robust authentication measures to ensure security in the ever-expanding e-world. This research aims to address ...
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In recent years, a variety of new frameworks streamlining the process of agent-based modeling has emerged. These frameworks serve different purposes and each offers a unique set of features. In this practical comparat...
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In a platoon communication scenario, the Platoon Leader (PL) vehicle interacts with the gNodeB (gNB) to obtain some assigned radio resources and then the obtained radio resources are allocated to the PL vehicle and it...
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The experiment was carried out by growing BaTiO3 (Undoped or Li-doped) on p-type Si(1 0 0) substrates using the Chemical Solution Deposition (CSD) method and spin coating at a rotational speed of 3000 rpm for 60 s, fo...
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Puzzle mats made of cushioned material are widely used in environments like homes and playrooms to prevent injuries from infants and toddlers falling. The mats feature puzzle-like edges, allowing users to freely adjus...
One of the most extensively used technologies for improving the security of IoT devices is blockchain *** is a new technology that can be utilized to boost the *** is a decentralized peer-to-peer network with no centr...
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One of the most extensively used technologies for improving the security of IoT devices is blockchain *** is a new technology that can be utilized to boost the *** is a decentralized peer-to-peer network with no central *** nodes on the network mine or verify the data recorded on the *** is a distributed ledger that may be used to keep track of transactions between several *** one can tamper with the data on the blockchain since it is *** the blocks are connected by hashes,the transaction data is *** is managed by a system that is based on the consensus of network users rather than a central *** immutability and tamper-proof nature of blockchain security is based on asymmetric cryptography and ***,Blockchain has an immutable and tamper-proof smart contract,which is a logic that enforces the Blockchain’s *** is a conflict between the privacy protection needs of cyber-security threat intelligent(CTI)sharing and the necessity to establish a comprehensive attack chain during blockchain *** paper presents a blockchain-based data sharing paradigm that protects the privacy of CTI sharing parties while also preventing unlawful sharing and ensuring the benefit of legitimate sharing *** builds a full attack chain using encrypted threat intelligence and exploits the blockchain’s backtracking capacity to finish the decryption of the threat source in the attack *** contracts are also used to send automatic early warning replies to possible attack *** tests are used to verify the feasibility and efficacy of the suggested model.
Classification of electroencephalogram(EEG)signals for humans can be achieved via artificial intelligence(AI)***,the EEG signals associated with seizure epilepsy can be detected to distinguish between epileptic and no...
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Classification of electroencephalogram(EEG)signals for humans can be achieved via artificial intelligence(AI)***,the EEG signals associated with seizure epilepsy can be detected to distinguish between epileptic and non-epileptic *** this perspective,an automated AI technique with a digital processing method can be used to improve these *** paper proposes two classifiers:long short-term memory(LSTM)and support vector machine(SVM)for the classification of seizure and non-seizure EEG *** classifiers are applied to a public dataset,namely the University of Bonn,which consists of 2 classes–seizure and *** addition,a fast Walsh-Hadamard Transform(FWHT)technique is implemented to analyze the EEG signals within the recurrence space of the ***,Hadamard coefficients of the EEG signals are obtained via the ***,the FWHT is contributed to generate an efficient derivation of seizure EEG recordings from non-seizure EEG ***,a k-fold cross-validation technique is applied to validate the performance of the proposed *** LSTM classifier provides the best performance,with a testing accuracy of 99.00%.The training and testing loss rates for the LSTM are 0.0029 and 0.0602,respectively,while the weighted average precision,recall,and F1-score for the LSTM are 99.00%.The results of the SVM classifier in terms of accuracy,sensitivity,and specificity reached 91%,93.52%,and 91.3%,*** computational time consumed for the training of the LSTM and SVM is 2000 and 2500 s,*** results show that the LSTM classifier provides better performance than SVM in the classification of EEG ***,the proposed classifiers provide high classification accuracy compared to previously published classifiers.
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