Automation software need to be continuously updated by addressing software bugs contained in their ***,bugs have different levels of importance;hence,it is essential to prioritize bug reports based on their sever-ity ...
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Automation software need to be continuously updated by addressing software bugs contained in their ***,bugs have different levels of importance;hence,it is essential to prioritize bug reports based on their sever-ity and *** managing the deluge of incoming bug reports faces time and resource constraints from the development team and delays the resolu-tion of critical ***,bug report prioritization is *** study pro-poses a new model for bug prioritization based on average one dependence estimator;it prioritizes bug reports based on severity,which is determined by the number of *** more the number of attributes,the more the *** proposed model is evaluated using precision,recall,F1-Score,accuracy,G-Measure,and Matthew’s correlation *** of the proposed model are compared with those of the support vector machine(SVM)and Naive Bayes(NB)*** and Mozilla datasetswere used as the sources of bug *** proposed model improved the bug repository management and out-performed the SVM and NB ***,the proposed model used a weaker attribute independence supposition than the former models,thereby improving prediction accuracy with minimal computational cost.
The droplet impact on the wall is a complex hydrodynamic process. After the droplet impact on the wall, it will undergo morphological changes such as spreading and rebound, which are closely related to the droplet cha...
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The potential to comfortable systems and networks from unauthorized get right of entry is essential for any virtual community. Authentication protocols are a cornerstone to protecting such structures from malicious ac...
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ISBN:
(纸本)9798350383348
The potential to comfortable systems and networks from unauthorized get right of entry is essential for any virtual community. Authentication protocols are a cornerstone to protecting such structures from malicious actors and imposing facts security. Despite the myriad of authentication protocols, however, there are boundaries to their efficacy in nicely securing digital networks. Authentication protocols, even those strongly encouraged through protection professionals, have recognized flaws and weaknesses which can be exploited by means attackers-resulting in violations of confidentiality, integrity, and availability of machine and application facts. Further, authentication protocols can be too hard to apply and cumbersome to maintain, main customers to bypass them-setting structures at risk and exposing them to capability breaches. This paper intends to research the strengths and weaknesses of authentication protocols and endorse techniques to maximize their effectiveness while deliberating applicability, usability, practicality, and cost. We can inspect adequate controls that can be used to bolster authentication protocols hired in existing facts protection models, as well as talk about the need for advanced authentication protocols and verification techniques. Authentication protocols are used in records protection fashions to offer cozy get right of entry to networked applications. Those protocols have to offer sturdy identification assurance and securely authenticate each gets the right of entry to try. This summary discusses the restrictions of the authentication protocols presently employed by current statistics protection fashions. Authentication protocols rely on cryptography and get admission to manipulate mechanisms to ensure that the most straightforward authenticated users gain access to sources. A few of the authentication protocols currently in use, including fundamental username and password authentication, are often a problem to assault due to thei
Diabetic foot ulcer (DFUs) are a common and significant consequence of diabetes, frequently resulting in severe illness and amputations if not promptly identified and treated. The growing occurrence of DFUs is a subst...
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The characterization of some important attributes in a given context is considered as one of the prominent issues for the decision making process. Same time another problem arises approximation of uncertainty and its ...
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Chronic Kidney Disease (CKD) is an increasingly common health issue, affecting a significant portion of the global population. Accurate prediction of CKD progression is crucial for early intervention and personalized ...
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Seeking effective numerical approximations for partial differential equations (PDEs) is a major challenge in modern science and technology. Recently, AI-inspired data-driven solvers, such as neural operators, have ach...
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In this internet era, cloud computing and there are various problems in the cloud computing, where the consumers as well as the service providers facing in their day to day cloud activities. Job scheduling problem pla...
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Recent advancements in blockchain-based cloud computing highlight its potential in providing robust data security, integrity, and confidentiality. While cloud computing is increasingly utilized for remote resource acc...
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Bot detection is considered a crucial security issue that is extensively analysed in various existingapproaches. Machine Learning is an efficient way of botnet attack detection. Bot detectionis the major issue faced b...
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Bot detection is considered a crucial security issue that is extensively analysed in various existingapproaches. Machine Learning is an efficient way of botnet attack detection. Bot detectionis the major issue faced by the existing system. This research concentrates on adopting a graphbasedfeature learning process to reduce feature dimensionality. The incoming samples arecorrectly classified and optimised using an Adaboost classifier with an improved grey wolfoptimiser (g-AGWO). The proposed IGWO optimisation approach is adopted to fulfil the multiconstraintissues related to bot detection and provide better local and global solutions (to satisfyexploration and exploitation). The extensive results show that the proposed g-AGWO model outperformsexisting approaches to reduce feature dimensionality, under-fitting/over-fitting andexecution time. The error rate prediction shows the feasibility of the given model to work over thechallenging environment. This model also works efficiently towards the unseen data to achievebetter generalization.
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