In recent decades,fog computing has played a vital role in executing parallel computational tasks,specifically,scientific workflow *** cloud data centers,fog computing takes more time to run workflow ***,it is essenti...
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In recent decades,fog computing has played a vital role in executing parallel computational tasks,specifically,scientific workflow *** cloud data centers,fog computing takes more time to run workflow ***,it is essential to develop effective models for Virtual Machine(VM)allocation and task scheduling in fog computing *** task scheduling,VM migration,and allocation,altogether optimize the use of computational resources across different fog *** process ensures that the tasks are executed with minimal energy consumption,which reduces the chances of resource *** this manuscript,the proposed framework comprises two phases:(i)effective task scheduling using a fractional selectivity approach and(ii)VM allocation by proposing an algorithm by the name of Fitness Sharing Chaotic Particle Swarm Optimization(FSCPSO).The proposed FSCPSO algorithm integrates the concepts of chaos theory and fitness sharing that effectively balance both global exploration and local *** balance enables the use of a wide range of solutions that leads to minimal total cost and makespan,in comparison to other traditional optimization *** FSCPSO algorithm’s performance is analyzed using six evaluation measures namely,Load Balancing Level(LBL),Average Resource Utilization(ARU),total cost,makespan,energy consumption,and response *** relation to the conventional optimization algorithms,the FSCPSO algorithm achieves a higher LBL of 39.12%,ARU of 58.15%,a minimal total cost of 1175,and a makespan of 85.87 ms,particularly when evaluated for 50 tasks.
Visual Place Recognition(VPR)technology aims to use visual information to judge the location of agents,which plays an irreplaceable role in tasks such as loop closure detection and *** is well known that previous VPR ...
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Visual Place Recognition(VPR)technology aims to use visual information to judge the location of agents,which plays an irreplaceable role in tasks such as loop closure detection and *** is well known that previous VPR algorithms emphasize the extraction and integration of general image features,while ignoring the mining of salient features that play a key role in the discrimination of VPR *** this end,this paper proposes a Domain-invariant information Extraction and Optimization Network(DIEONet)for *** core of the algorithm is a newly designed Domain-invariant information Mining Module(DIMM)and a Multi-sample Joint Triplet Loss(MJT Loss).Specifically,DIMM incorporates the interdependence between different spatial regions of the feature map in the cascaded convolutional unit group,which enhances the model’s attention to the domain-invariant static object *** Loss introduces the“joint processing of multiple samples”mechanism into the original triplet loss,and adds a new distance constraint term for“positive and negative”samples,so that the model can avoid falling into local optimum during *** demonstrate the effectiveness of our algorithm by conducting extensive experiments on several authoritative *** particular,the proposed method achieves the best performance on the TokyoTM dataset with a Recall@1 metric of 92.89%.
A sandwich plate with a corrugation and auxetic honeycomb hybrid core is constructed,and its sound insulation and optimization are ***,the motion governing equation of the sandwich plate is established by the third-or...
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A sandwich plate with a corrugation and auxetic honeycomb hybrid core is constructed,and its sound insulation and optimization are ***,the motion governing equation of the sandwich plate is established by the third-order shear deformation theory(TSDT),and then combined with the fluid-structure coupling conditions,and the sound insulation is *** theoretical results are validated by COMSOL simulation results,and the effects of the structural parameter on the sound insulation are ***,the standard genetic algorithm is adopted to optimize the sound insulation of the sandwich plate.
Dwell scheduling is a key for phased array radar to realize multi-function and it becomes especially challenging in complex tactical *** this manuscript,a real-time radar dwell scheduling algorithm based on a unified ...
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Dwell scheduling is a key for phased array radar to realize multi-function and it becomes especially challenging in complex tactical *** this manuscript,a real-time radar dwell scheduling algorithm based on a unified pulse interleaving framework is proposed.A unified pulse interleaving framework that can realize pulse interleaving analysis for phased array radars with different receiving modes is put forward,which greatly improves the time utilization of the *** on above framework,a real-time two-stage approach is proposed to solve the optimization problem of dwell *** importance and urgency criteria are guaranteed by the first pre-schedule stage,and the desired execution time criterion is improved at the second stage with the modified particle swarm optimization(PSO).Simulation results demonstrate that the proposed algorithm has better comprehensive scheduling performance than up-to-date algorithms that consider the pulse interleaving technique for both single beam and multiple beams receiving ***,the proposed algorithm can realize dwell scheduling in realtime.
In the industrial Internet of things(IIoT), various applications generate a large number of interactions and are vulnerable to various attacks, which are difficult to be monitored in a sophisticated way by traditional...
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In the industrial Internet of things(IIoT), various applications generate a large number of interactions and are vulnerable to various attacks, which are difficult to be monitored in a sophisticated way by traditional network architectures. Therefore, deploying software-defined network(SDN) in IIoT is essential to defend against various attacks. However, SDN has a drawback: there is a security problem of distributed denial-ofservice(DDoS) attacks at the control layer. This paper proposes an effective solution: DDoS detection within the domain using tri-entropy in information theory. The detected attacks are then uploaded to a smart contract in the blockchain, so that the attacks can be quickly cut off even if the same attack occurs in different domains. Experimental validation was conducted under different attack strengths and multiple identical attacks, and the results show that the method has better detection ability under different attack strengths and can quickly block the same attacks.
Deep learning technology has extensive application in the classification and recognition of medical images. However, several challenges persist in such application, such as the need for acquiring large-scale labeled d...
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Proposing a performance testing methodology for vehicle collision warning algorithm at intersections, this approach addresses the issues of the key V2X technology being challenging to simulate with real-scene data in ...
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Fluorescence imaging techniques represent essential tools in in vitro,preclinical,and clinical *** this study,an improved one-step hydrothermal method to synthesize citric acid(CA)modifiedα-NaYbF_(4):2%Er^(3+)nanocry...
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Fluorescence imaging techniques represent essential tools in in vitro,preclinical,and clinical *** this study,an improved one-step hydrothermal method to synthesize citric acid(CA)modifiedα-NaYbF_(4):2%Er^(3+)nanocrystals was *** introduction of various doping ions into NaYbF_(4):2%Er^(3+)and the different valence states of the same ions affect both the crystal size and upconversion luminesce *** fore,we investigated the upconversion luminesce nce enha ncement of NaYbF_(4):2%Er^(3+)by ion doping and find that the upconversion luminescence intensity of the upconversion nanoparticles(UCNPs)co-doped with 5 mol%Fe^(2+)ions shows the greatest enhancement,especially for red emission at654 ***,HeLa cells incubated with UCNPs allow for imaging with strong red upconversion emission detectio *** laser scanning microscope(CLSM)fluorescent images of HeLa cells indicate that NaYbF_(4):2%Er/5%Fe^(2+)leads to a clear outline and improves visualization of the cell *** addition,the CA coated NaYbF_(4):2%Er^(3+)/5%Fe^(2+)nanoparticles and NaYbF_(4):2%Er^(3+)/5%Fe^(2+)show low cytotoxicity in HeLa *** imaging reveals the efficiency of these UCNPs to analyze the lungs,liver,and ***,these results indicate that the Cit-NaYbF_(4):2%Er^(3+)/5%Fe^(2+)UCNPs are efficient nanoprobes for fluorescence molecular to mography.
The self-supervised monocular depth estimation algorithm obtains excellent results in outdoor environments. However, traditional self-supervised depth estimation methods often suffer from edge blurring in complex text...
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Mashup developers often need to find open application programming interfaces(APIs) for their composition application development. Although most enterprises and service organizations have encapsulated their businesses ...
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Mashup developers often need to find open application programming interfaces(APIs) for their composition application development. Although most enterprises and service organizations have encapsulated their businesses or resources online as open APIs, finding the right high-quality open APIs is not an easy task from a library with several open APIs. To solve this problem, this paper proposes a deep learning-based open API recommendation(DLOAR) approach. First, the hierarchical density-based spatial clustering of applications with a noise topic model is constructed to build topic models for Mashup clusters. Second,developers' requirement keywords are extracted by the Text Rank algorithm, and the language model is built. Third, a neural network-based three-level similarity calculation is performed to find the most relevant open APIs. Finally, we complement the relevant information of open APIs in the recommended list to help developers make better choices. We evaluate the DLOAR approach on a real dataset and compare it with commonly used open API recommendation approaches: term frequency-inverse document frequency, latent dirichlet allocation, Word2Vec, and Sentence-BERT. The results show that the DLOAR approach has better performance than the other approaches in terms of precision, recall, F1-measure, mean average precision,and mean reciprocal rank.
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