This study addresses the challenges of real-time data synchronization and big data processing in the construction of digital twin workshops under the background of intelligent manufacturing. A solution that integrates...
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The rise of e-banking and plastic money has increased the risk of account takeover fraud, resulting in unauthorized transactions and identity theft. To counter this, the paper suggests using artificial immune systems ...
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Blind symbol rate estimation is crucial for adaptive communication systems and cognitive radios. This paper presents a novel approach to tackle blind symbol rate estimation from received complex baseband signals. The ...
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The innovative technology for physiotherapy assessment employing deep learning aims to offer a precise and streamlined approach to evaluating physiotherapy needs. Conventional manual assessment techniques utilized in ...
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The proposed study evaluates the critical role of machine learning (ML) algorithms in predicting renal function decline in individuals with chronic kidney disease (CKD). The crucial need originates from the limitation...
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Automatically describing the content of a picture with meaningful and contextually appropriate textual descriptions is a difficult challenge at the interface of computer vision and natural language processing. This re...
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This research investigates the integration of machine learning (ML) into traditional agricultural practices to address the challenges posed by conventional methods. The study begins by examining the limitations of tra...
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teaching collaboration between universities is becoming increasingly important. Student intakes are increasing, and students are including MOOC courses from other universities to their studies. In Finland, there has b...
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In dynamic software development, ensuring high reliability and quality is an important goal. The biggest challenge in this field is the early detection and correction of errors, which if not addressed in time can lead...
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Wireless Sensor Networks (WSNs) often rely on constrained devices with limited processor and power resources. Therefore, many approaches in the literature have studied data reduction methods to relieve these resources...
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