The exponential growth of the number of devices connected to the Internet and the use of IoT applications increases the amount of data exchange over public channels in low-cost and low-power embedded systems. Images a...
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The box office (BO) income had significantly declined up to 80% in 2020, as the COVID-19 pandemic emerged. To minimize further financial risks, multiplex (multiple cinema complexes) owners need to analyze their potent...
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The projected increase in PayLater utilization reaches up to five million people by 2025. To optimize the yearly profit from their PayLater service, fintech companies must examine all possible risks before a unanimous...
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Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict softwa...
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Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict software bugs,but a more precise and general approach is *** bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning ***,these studies are not generalized and efficient when extended to other ***,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification *** methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a *** National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were *** reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.
The growing focus on microcredentials emphasizes the urgent need for precise and widely accepted definitions, as existing uncertainties hinder their effective implementation. This research aims to investigate the comp...
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Task oriented chatbots are a sub-topic related to chatbots, where chatbots will perform certain tasks with specific goals. One part of creating a task-oriented chatbot is doing intent classification. Intent classifica...
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This research discusses the performance evaluation of distributed database systems in a cloud computing environment Cloud computing environments allow data and applications to be stored and deployed on infrastructure ...
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The study aims to fill existing research gaps by creating a new framework that explores the impact of social media influencers on sustainable usage patterns, focusing on business sustainability as a mediating factor. ...
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For both print and digital media, the accuracy of the information has long been a problem that has impacted society and the business world. Information travels so quickly on social networks and is amplified that it ca...
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Minimizing time wastage is a crucial objective for all production operations. Reliable manufacturing scheduling The objective is to mitigate time-based production waste caused by excessive processing, waiting, and tra...
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