The accumulation of large datasets by the scientific community has surpassed the capacity of traditional processing methods, underscoring the critical need for innovative and efficient algorithms capable of nav
This technique allows quantum models to better capture complex patterns, such as traffic dynamics, by repeatedly encoding classical data into a quantum state. Aside from providing a prediction model, we spend considerable effort in comparing the performance of our hybrid quantum-classical neural ...
Looking forward, AI will be increasingly integrated into analytics tools,data managementworkflows and business operations. AI-powered systems will move toward being able to autonomously monitor data, identify significant patterns and either take actions themselves or alert business stakeholders. Theseagent...
Furthermore, the encoding and decoding operation is blind: it does not depend on knowledge of the exact states being transmitted. This is a powerful general result. No assumptions about the exact nature of the quantum states is made. For example, the quantum states need not be orthogonal. If...
At present, there are two competing system architectures for quantum computing; there is the gate model (aka quantum circuit) and adiabatic quantum computing (AQC). Although they are different architectures, they have been shown mathematically shown to be equivalent in that both architectures will op...
Through a linear node encoding layer and two-layer DeeperGCN network architecture with residual connections, the model is able to pass and enhance the association features among nodes layer by layer, effectively capturing the complex interaction patterns and structural properties in cellular networks. ...
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File Activity Monitoring:Data Security Software should be capable of monitoring data usage patterns across all users to detect anomalies and potential risks early. In particular, over-permission may give users more access to data than necessary for their roles within an organization; data security sof...
Use of transfer learning for efficient feature extraction: using pre-trained models that help recognize patterns makes our training consume less time and makes our results less prone to overfitting. ELMs with optimized hidden layer size: This study adapts ELMs to handle the particularities of MC cla...
One more object of the present invention is to provide efficient and effective encoding and decoding circuitry for use within a digital ASIC of a PR4, ML channel, such as a disk drive read and write channel. In accordance with principles of the present invention, a serializing/deserializing enc...