RFID technologies have been widely used in various applications in recent decades. This includes smart healthcare. Authenticating users is essential in healthcare applications for safety, security, data confidentialit...
详细信息
The efficiency and reliability of engine parts are largely governed by friction. The valve train assembly is considered one of the extremely difficult assemblies in terms of its tribological performance and is often s...
详细信息
We build upon recent work on the use of machine-learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supe...
详细信息
We build upon recent work on the use of machine-learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning, where the weak-measurement training record can be labeled with known Hamiltonian parameters, and (2) unsupervised learning, where no labels are available. The first has the advantage of not requiring an explicit representation of the quantum state, thus potentially scaling very favorably to a larger number of qubits. The second requires the implementation of a physical model to map the Hamiltonian parameters to a measurement record, which we implement using an integrator of the physical model with a recurrent neural network to provide a model-free correction at every time step to account for small effects not captured by the physical model. We test our construction on a system of two qubits and demonstrate accurate prediction of multiple physical parameters in both the supervised context and the unsupervised context. We demonstrate that the model benefits from larger training sets, establishing that it is “learning,” and we show robustness regarding errors in the assumed physical model by achieving accurate parameter estimation in the presence of unanticipated single-particle relaxation.
Ordinary differential equations (ODEs) are a fundamental tool for modeling dynamical systems in various scientific fields. However, solving ODEs analytically can be challenging, and numerical methods can be computatio...
详细信息
This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They h...
详细信息
We present an algorithm for computing semistable degeneration of double octic Calabi-Yau threefolds. Our method has a combinatorial representation by the means of double octic diagrams. The proposed algorithm is appli...
详细信息
The system deadlock problem of the flexible manufacturing system (FMS) needs to be solved urgently. Deadlocks may occur when resources are repeatedly requested by multiple working processes, where such competition cau...
详细信息
This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB 2024). The competition attracted a total of ten regis...
详细信息
This paper introduces an improved version of well-known Sooty Tern Optimization Algorithm (STOA). The improved version combines Opposition based learning (OBL) to introduce the Improved Sooty Tern Optimization Algorit...
详细信息
Banking produces extensive and diverse data, so a clustering process is needed to understand customer behavior patterns and transactions more effectively. This clustering has been widely utilized with the K-Means algo...
详细信息
暂无评论