Distributed systems and blockchain consensus protocols rely on a clock synchronization algorithm to resolve any conflicts related to the state of data or resources. Faulty and adversarial peers make it challenging to ...
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Heart disease (HD) stands as a major global health challenge, being a predominant cause of death and demanding intricate and costly detection methods. The widespread impact of heart failure, contributing to increased ...
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Synthetic genome evolution provides a dynamic approach for systematically and straightforwardly exploring evolutionary *** Chromosome Rearrangement and Modification by LoxP-mediated Evolution(SCRaMbLE) is an evolution...
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Synthetic genome evolution provides a dynamic approach for systematically and straightforwardly exploring evolutionary *** Chromosome Rearrangement and Modification by LoxP-mediated Evolution(SCRaMbLE) is an evolutionary system intrinsic to the synthetic yeast genome that can rapidly drive structural ***,we detect over 260 000 rearrangement events after the SCRaMbLEing of a yeast strain harboring 5.5 synthetic yeast chromosomes(synⅡ,synⅢ,synⅤ,circular synⅥ,synⅨR and synⅩ).Remarkably,we find that the rearrangement events exhibit a specific landscape of *** further reveal that the landscape is shaped by the combined effects of chromatin accessibili and spatial contact *** rearrangements tend to occur in 3D spatially proximal and chromatin-accessible *** enormous numbers of rearrangements mediated by SCRaMbLE provide a driving force to potentiate directed genome evolution,and the investigation of the rearrangement landscape offers mechanistic insights into the dynamics of genome evolution.
The medical community has more concern on lung cancer *** experts’physical segmentation of lung cancers is time-consuming and needs to be *** research study’s objective is to diagnose lung tumors at an early stage t...
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The medical community has more concern on lung cancer *** experts’physical segmentation of lung cancers is time-consuming and needs to be *** research study’s objective is to diagnose lung tumors at an early stage to extend the life of humans using deep learning ***-Aided Diagnostic(CAD)system aids in the diagnosis and shortens the time necessary to detect the tumor *** application of Deep Neural Networks(DNN)has also been exhibited as an excellent and effective method in classification and segmentation *** research aims to separate lung cancers from images of Magnetic Resonance Imaging(MRI)with threshold *** Honey hook process categorizes lung cancer based on characteristics retrieved using several *** this principle,the work presents a solution for image compression utilizing a Deep Wave Auto-Encoder(DWAE).The combination of the two approaches significantly reduces the overall size of the feature set required for any future classification process performed using *** proposed DWAE-DNN image classifier is applied to a lung imaging dataset with Radial Basis Function(RBF)*** study reported promising results with an accuracy of 97.34%,whereas using the Decision Tree(DT)classifier has an accuracy of 94.24%.The proposed approach(DWAE-DNN)is found to classify the images with an accuracy of 98.67%,either as malignant or normal *** contrast to the accuracy requirements,the work also uses the benchmark standards like specificity,sensitivity,and precision to evaluate the efficiency of the *** is found from an investigation that the DT classifier provides the maximum performance in the DWAE-DNN depending on the network’s performance on image testing,as shown by the data acquired by the categorizers themselves.
With the flexible deployment and high mobility of Unmanned Aerial Vehicles(UAVs)in an open environment,they have generated con-siderable attention in military and civil applications intending to enable ubiquitous conn...
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With the flexible deployment and high mobility of Unmanned Aerial Vehicles(UAVs)in an open environment,they have generated con-siderable attention in military and civil applications intending to enable ubiquitous connectivity and foster agile *** difficulty stems from features other than mobile ad-hoc network(MANET),namely aerial mobility in three-dimensional space and often changing *** the UAV network,a single node serves as a forwarding,transmitting,and receiving node at the same ***,the communication path is multi-hop,and routing significantly affects the network’s performance.A lot of effort should be invested in performance analysis for selecting the optimum routing *** this motivation,this study modelled a new Coati Optimization Algorithm-based Energy-Efficient Routing Process for Unmanned Aerial Vehicle Communication(COAER-UAVC)*** presented COAER-UAVC technique establishes effective routes for communication between the *** is primarily based on the coati characteristics in nature:if attacking and hunting iguanas and escaping from ***,the presented COAER-UAVC technique concentrates on the design of fitness functions to minimize energy utilization and communication delay.A varied group of simulations was performed to depict the optimum performance of the COAER-UAVC *** experimental results verified that the COAER-UAVC technique had assured improved performance over other approaches.
Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secu...
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As industrial models and designs grow increasingly complex, the demand for optimal control of large-scale dynamical systems has significantly increased. However, traditional methods for optimal control incur significa...
The advent of Ultra-Low-Latency storage devices has narrowed the performance gap between storage and CPU in computing platforms, facilitating synchronous I/O adoption. Yet, this approach introduces substantial busy wa...
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The accurate and rapid transfer of complex urban spatiotemporal data is crucial for urban computing tasks such as urban planning and public transportation deployment for smart-city applications. Existing works conside...
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Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of mult...
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Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BHJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,HBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BHJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BHJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BHJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BHJOalgorithmabout its counterparts,shedd
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