395 research outputs found
Data-driven Models for Inferring the Patient Scheduling Policies via Inverse Reinforcement Learning
No full textIn this work, we study multi-class patient scheduling with stochastic daily patient arrivals. Different classes of patients are characterized by different service times, waiting cost parameters, and rejection cost parameters. Our primary objective is to infer the policy used by the decision-makers, who schedule patients over a finite time horizon, based on their historical decisions. To achieve this, we first develop a mathematical model that captures the complexities of patient scheduling and is representative of the problem that decision-makers may consider to scheduling patients. Then, we utilize the Riccati and Hamiltonian approaches to estimate the cost parameters that have influenced the scheduling decisions made by the decision-maker. The Riccati approach begins by estimating the expert's policy, which is then used to determine the cost parameters. Conversely, the Hamiltonian approach derives the cost parameters through the optimality conditions of a path trajectory without needing to estimate the expert's policy. Using a simulation model, we demonstrate the efficiency and robustness of the proposed methods.
Furthermore, we apply Riccati and Hamiltonian approaches to MRI data from two hospitals to estimate the cost parameters used in their scheduling decisions.
Utilizing the estimated cost parameters, we analyze the root causes of the observed outcomes and examine the impact of these underlying factors on the scheduling process.
Finally, through counterfactual analysis, we propose two alternative scheduling policies that reduce the total cost, even with the original cost parameters used by the decision-makers
A COMMON FIXED POINT FOR WEAK φ-CONTRACTIONS ON <i>b</i>-METRIC SPACES
No full textaydi, hassen/0000-0003-4606-7211; Moradi, Sirous/0000-0002-8640-7252; , Hassen/0000-0003-3896-3809In this paper, we give a common fixed point result, for single-valued and multi-valued mappings satisfying a weak phi-contraction in b-metric spaces. Presented theorems extend, generalize and improve some existing results in the literature. Some examples are also given.Romanian National Authority for Scientific Research, CNCS UEFISCDI [PN-II-ID-PCE-2011-3-0094]The second author is partially supported by a grant of the Romanian National Authority for Scientific Research, CNCS UEFISCDI, project number PN-II-ID-PCE-2011-3-0094.Science Citation Index Expande
A Spatiotemporal Deep Neural Network Useful for Defect Identification and Reconstruction of Artworks Using Infrared Thermography
No full textAssessment of cultural heritage assets is now extremely important all around the world. Non-destructive inspection is essential for preserving the integrity of artworks while avoiding the loss of any precious materials that make them up. The use of Infrared Thermography is an interesting concept since surface and subsurface faults can be discovered by utilizing the 3D diffusion inside the object caused by external heat. The primary goal of this research is to detect defects in artworks, which is one of the most important tasks in the restoration of mural paintings. To this end, machine learning and deep learning techniques are effective tools that should be employed properly in accordance with the experiment’s nature and the collected data. Considering both the temporal and spatial perspectives of step-heating thermography, a spatiotemporal deep neural network is developed for defect identification in a mock-up reproducing an artwork. The results are then compared with those of other conventional algorithms, demonstrating that the proposed approach outperforms the others
A novel collaborative filtering model based on combination of correlation method with matrix completion technique
No full text
A Fountain of Sasanian Age from Ardashir Khwarrah, with a note on the Archaeometric Investigations by Maria Letizia Amadori
No full textThe author describes a peculiar stone object preserved in the stores of Firuzabad UNESCO site base, and tries to interpet and date it as a fountain of the Sasanian period
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