Despite the significant advancements in drone sensory device reliability, data integrity from these devices remains critical in securing successful flight plans. A notable issue is the vulnerability of GNSS to jamming attacks or signal loss from satellites, potentially leading to incomplete drone flight plans. To address this, we introduce SiaN-VO, a Siamese neural network designed for visual odometry prediction in such challenging scenarios.
View Article and Find Full Text PDFThe lack of precision to predict service performance through load indices may lead to wrong decisions regarding the use of web services, compromising service performance and raising platform cost unnecessarily. This paper presents experimental studies to qualify the behaviour of load indices in the web service context. The experiments consider three services that generate controlled and significant server demands, four levels of workload for each service and six distinct execution scenarios.
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