This is a repository copy of CME arrival time prediction using convolutional neural network.

There has been a dramatic increase over the past decade in the number of firms that source finished product from overseas. While this has reduced procurement costs, it has increased supply risk; procurement lead times are longer and are often unreliable. In deciding when and how much to order, firms must consider the lead time risk and the demand risk, i.e., the accuracy of their demand forecast. To improve the accuracy of its demand forecast, a firm may update its forecast as the selling season approaches. In this paper we consider both forecast updating and lead time uncertainty. We characterize the firm's optimal procurement policy, and we prove that, with multiplicative forecast revisions, the firm's optimal procurement time is independent of the demand forecast evolution but that the optimal procurement quantity is not. This leads to a number of important managerial insights into the firm's planning process. We show that the firm becomes less sensitive to lead time variability as the forecast updating process becomes more efficient. Interestingly, a forecast-updating firm might procure earlier than a firm with no forecast updating.

The primary objective of this study is to evaluate the applicability and the effectiveness of ground-penetrating radar (GPR) to identify a thin burnt soil layer, buried more than 2 m below the topographic surface at the Liangzhu Site, in Southeastern China. The site was chosen for its relatively challenging conditions of GPR techniques due to electrical conductivity and to the presence of peach tree roots that produced scattering. We completed the data acquisition by using 100 and 200 MHz antennas in TE and TM broadside and cross-polarized configurations. In the data processing and interpretation phase, we used GPR attribute analysis, including instantaneous phase and geometrical attributes. Validation analysis ground-truthing performed after the geophysical surveys, validated the GPR imaging, confirmed the electrical conductivity and relative dielectric permittivity (RDP) measurements performed at different depths, and allowed a reliable quantitative correlation between GPR results and subsurface physical properties. The research demonstrates that multiple antenna configurations in GPR data acquisition combined with attribute analysis can enhance the ability to characterize prehistoric archaeological remains even in complex subsurface conditions.

The latest technological progress of achieving the ultrastrong-coupling regime in circuit quantum electrodynamics (QED) systems has greatly promoted the developments of quantum physics, where novel quantum optics phenomena and potential computational benefits have been predicted. Here, we propose a scheme to accelerate the nontrivial two-qubit phase gate in a circuit QED system, where superconducting flux qubits are ultrastrongly coupled to a transmission line resonator (TLR), and two more TLRs are coupled to the ultrastrongly-coupled system for assistant. The nontrivial unconventional geometric phase gate between the two flux qubits is achieved based on close-loop displacements of the three-mode intracavity fields. Moreover, as there are three resonators contributing to the phase accumulation, the requirement of the coupling strength to realize the two-qubit gate can be reduced. Further reduction in the coupling strength to achieve a specific controlled-phase gate can be realized by adding more auxiliary resonators to the ultrastrongly-coupled system through superconducting quantum interference devices. We also present a study of our scheme with realistic parameters considering imperfect controls and noisy environment. Our scheme possesses the merits of ultrafastness and noise-tolerance due to the advantages of geometric phases.