Multi-label learning deals with objects associated with multiple class labels,and aims to induce a predictive model which can assign a set of relevant class labels for an unseen *** each class might possess its own ch...
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Multi-label learning deals with objects associated with multiple class labels,and aims to induce a predictive model which can assign a set of relevant class labels for an unseen *** each class might possess its own characteristics,the strategy of extracting label-specific features has been widely employed to improve the discrimination process in multi-label learning,where the predictive model is induced based on tailored features specific to each class label instead of the identical instance *** a representative approach,LIFT generates label-specific features by conducting clustering ***,its performance may be degraded due to the inherent instability of the single clustering *** improve this,a novel multi-label learning approach named SENCE(stable label-Specific features gENeration for multi-label learning via mixture-based Clustering Ensemble)is proposed,which stabilizes the generation process of label-specific features via clustering ensemble ***,more stable clustering results are obtained by firstly augmenting the original instance repre-sentation with cluster assignments from base clusters and then fitting a mixture model via the expectation-maximization(EM)*** experiments on eighteen benchmark data sets show that SENCE performs better than LIFT and other well-established multi-label learning algorithms.
Dengue fever is a common vector-borne sickness in tropical regions, particularly in India, Bangladesh, and Pakistan. This disease, caused by mosquitoes, affects people of all ages in more than a hundred nations throug...
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This study presents a novel approach to quantifying physical exertion using various machine learning algorithms. Such techniques include, among others, random forests, decision trees, linear regression, and gradient b...
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In recent years, rapid advancements in hardware and deep learning technologies have paved the way for the extensive integration of image recognition and object detection into daily applications. As reliance on deep le...
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Unmanned aerial vehicles offer services such as military reconnaissance in potentially adversarial controlled *** addition,they have been deployed in civilian critical infrastructure *** this environment,real-time and...
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Unmanned aerial vehicles offer services such as military reconnaissance in potentially adversarial controlled *** addition,they have been deployed in civilian critical infrastructure *** this environment,real-time and massive data is exchanged between the aerial vehicles and the ground control *** on the mission of these aerial vehicles,some of the collected and transmitted data is sensitive and ***,many security protocols have been presented to offer privacy and security ***,majority of these schemes fail to consider attack vectors such as side-channeling,de-synchronization and known secret session temporary information *** last attack can be launched upon adversarial physical capture of these *** addition,some of these protocols deploy computationally intensive asymmetric cryptographic primitives that result in high *** this paper,an authentication protocol based on lightweight quadratic residues and hash functions is *** formal security analysis is executed using the widely deployed random oracle *** addition,informal security analysis is carried out to show its robustness under the Dolev–Yao(DY)and Canetti–Krawczyk(CK)threat *** terms of operational efficiency,it is shown to have relatively lower execution time,communication costs,and incurs the least storage costs among other related ***,the proposed protocol provides a 25%improvement in supported security and privacy features and a 6.52%reduction in storage *** overall,the proposed methodology offers strong security and privacy protection at lower execution time,storage and communication overheads.
As the globe transitions to the internet age, software has emerged as the factor primarily essential to the success of the digital realm. Software now permeates every aspect of daily existence in the age of computers....
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In recent years, skin cancer is a frequent and dangerous disease that requires rapid and accurate analysis to secure effective treatment. Accurate detection and diagnosis of skin lesions is challenging due to the simi...
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Tiger conservation requires integrating diverse strategies, including preserving natural habitats, stringent anti-poaching efforts, and active community participation to ensure sustainable tiger population growth. The...
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In the past few years,social media and online news platforms have played an essential role in distributing news content *** of the authenticity of news has become a major *** the COVID-19 outbreak,misinformation and f...
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In the past few years,social media and online news platforms have played an essential role in distributing news content *** of the authenticity of news has become a major *** the COVID-19 outbreak,misinformation and fake news were major sources of confusion and insecurity among the general *** the first quarter of the year 2020,around 800 people died due to fake news relevant to *** major goal of this research was to discover the best learning model for achieving high accuracy and performance.A novel case study of the Fake News Classification using ELECTRA model,which achieved 85.11%accuracy score,is thus reported in this *** addition to that,a new novel dataset called COVAX-Reality containing COVID-19 vaccine-related news has been *** the COVAX-Reality dataset,the performance of FNEC is compared to several traditional learning models i.e.,Support Vector Machine(SVM),Naive Bayes(NB),Passive Aggressive Classifier(PAC),Long Short-Term Memory(LSTM),Bi-directional LSTM(Bi-LSTM)and Bi-directional Encoder Representations from Transformers(BERT).For the evaluation of FNEC,standard metrics(Precision,Recall,Accuracy,and F1-Score)were utilized.
Recent advancements in cloud computing(CC)technologies signified that several distinct web services are presently developed and exist at the cloud data ***,web service composition gains maximum attention among researc...
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Recent advancements in cloud computing(CC)technologies signified that several distinct web services are presently developed and exist at the cloud data ***,web service composition gains maximum attention among researchers due to its significance in real-time *** of Service(QoS)aware service composition concerned regarding the election of candidate services with the maximization of the whole *** these models have failed to handle the uncertainties of *** resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by *** the other hand,trip planning is an essential technique in supporting digital map *** aims to determine a set of location based services(LBS)which cover all client intended activities quantified in the *** the available web service composition solutions do not consider the complicated spatio-temporal *** resolving this issue,this study develops a new hybridization of the firefly optimization algorithm with fuzzy logic based web service composition model(F3L-WSCM)in a cloud environment for location *** presented F3L-WSCM model involves a discovery module which enables the client to provide a query related to trip planning such as flight booking,hotels,car rentals,*** the next stage,the firefly algorithm is applied to generate composition plans to minimize the number of composition *** by,the fuzzy subtractive clustering(FSC)will select the best composition plan from the available composite ***,the presented F3L-WSCM model involves four input QoS parameters namely service cost,service availability,service response time,and user *** extensive experimental analysis takes place on CloudSim tool and exhibit the superior performance of the presented F3L-WSCM model in terms of accuracy,execution time,and efficiency.
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