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Nowadays, very large quantities of data are produced both individually and institutionally. These data must be preserved very well in order to be able to access and process them as needed. This situation necessitates data recovery services in possible disast…

The purpose of this study is to examine the software libraries and data sets used for Deep Learning architectures. Deep Learning brings a different perspective to the field of artificial intelligence. It has begun to be used an incredibly wide field in recent …

In this study, a classification problem is discussed to predict whether individuals' annual income levels are above $50,000. The UCI Adult Income Dataset, which is derived from the 1994 US Census (Census) data and is widely used in the field of machine learnin…

Post-quantum cryptographic standardization is complete for the algorithms that matter most, yet adoption across financial infrastructure remains uneven and, in critical segments, largely absent. This paper argues that migration is no longer a research question…

In the contemporary era of technological advancements, integrating Generative Artificial Intelligence (AI) with radar systems has emerged as a groundbreaking approach to enhance the quality and clarity of radar data. This fusion has paved the way for significa…

Seismic data is a critical source for examining and understanding subsurface structures. It is used in various fields such as oil exploration, geological research, mining, underground infrastructure planning, environmental monitoring, and conservation. The ana…