Monitoring the degradation of induction motors is an essential concern for industries, especially when there are high costs related to maintenance and their stops. Nowadays, there are many non-invasive ways to monitor...
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Protein Structure Prediction (PSP) problem is an open problem in bioinformatics and, as the problem scales, complexity and processing time increases. In this way, robust methods and massively parallel architectures ar...
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This study introduces the Quantum-Train Quantum Fast Weight programmer (QT-QFWP) framework, enabling efficient and scalable programming of variational quantum circuits (VQCs) through quantum-driven parameter updates f...
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ISBN:
(数字)9798331531591
ISBN:
(纸本)9798331531607
This study introduces the Quantum-Train Quantum Fast Weight programmer (QT-QFWP) framework, enabling efficient and scalable programming of variational quantum circuits (VQCs) through quantum-driven parameter updates for the classical slow programmer controlling the fast programmer VQC. By optimizing quantum and classical parameter management, QT-QFWP significantly reduces parameters (by 70–90%) compared to Quantum Long Short-Term Memory (QLSTM) and Quantum Fast Weight programmer (QFWP) while maintaining accuracy. Benchmarking on time-series tasks—including Damped Simple Harmonic Motion (SHM), NARMA5, and Simulated Gravitational Waves (GW)—demonstrates superior efficiency and predictive accuracy. QT-QFWP is particularly advantageous for near-term quantum systems, addressing qubit and gate fidelity constraints, enhancing VQC deployment in time-sensitive applications, and expanding quantum computing’s role in machine learning.
Elasticity is one of the most known capabilities related to cloud computing, being largely deployed using thresholds. In this way, limits are used to drive resource mangement actions, leading to the following problem ...
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Clocking represents the manner in which companies register employee data;particularly, data related to entrances to and departures from the company. Being normally implemented with wireless cards or by hand, this proc...
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Digital road maps have gained fundamental role in population's daily life, so they need to be accurate and up-to-date. A viable solution is to generate maps by processing GPS data. However, one of the most challen...
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Digital road maps have gained fundamental role in population's daily life, so they need to be accurate and up-to-date. A viable solution is to generate maps by processing GPS data. However, one of the most challenging tasks regarding this approach is how to extract road centerlines from the cloud of georeferenced GPS points. The literature presents various methods that do it, but none have been found that is prepared for the continuous update of the map and refinement of its roads' accuracy. In this context, the objective of this work is to propose a method to identify road centerlines using an evolutive algorithm in order to generate and update road maps. This work uses as source of data GPS traces collected by smartphones. Although suitable to obtain a large amount of georeferenced data, these devices bring the additional problem of identifying the transport vehicle used along each trace. Preliminary results indicate that the method's performance is satisfactory, with an average variation of 2.95 meters in relation to satellite images.
As a result of rural and suburban migration to the cities, urban life has become a significant challenge for citizens and mayors, imposing a huge concern in the sustainable use of resources like energy, water, transpo...
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This paper aims to identify and analyze recommender systems developed for the health area, available in mobile applications. Therefore, literature was reviewed systematically from ACM, IEEE, Springer and Science Direc...
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The use of recommender systems is widespread in several everyday systems. People are now exposed to different offerings, based on their interests, in order to anticipate decisions. However, in a different way recommen...
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