Gibbs sampling for multipath arrival time estimation in an uncertain environment

2003 ◽  
Vol 113 (4) ◽  
pp. 2271-2271
Author(s):  
Michele Picarelli ◽  
Zoi‐Heleni Michalopoulou
Keyword(s):  
Gibbs Sampling ◽  
Arrival Time ◽  
Time Estimation ◽  
Uncertain Environment

scholarly journals Short-Term Scheduling Model of Cluster Tool in Wafer Fabrication

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1029
Author(s):  
Ying-Mei Tu
Keyword(s):  
Arrival Time ◽  
Time Estimation ◽  
Advanced Technology ◽  
Shop Floor ◽  
Process Time ◽  
Short Term ◽  
Work In Process ◽  
Scheduling Model ◽  
Cluster Tools ◽  
Cluster Tool

Since last decade, the cluster tool has been mainstream in modern semiconductor manufacturing factories. In general, the cluster tool occupies 60% to 70% of production machines for advanced technology factories. The most characteristic feature of this kind of equipment is to integrate the relevant processes into one single machine to reduce wafer transportation time and prevent wafer contaminations as well. Nevertheless, cluster tools also increase the difficulty of production planning significantly, particularly for shop floor control due to complicated machine configurations. The main objective of this study is to propose a short-term scheduling model. The noteworthy goal of scheduling is to maximize the throughput within time constraints. There are two modules included in this scheduling model—arrival time estimation and short-term scheduling. The concept of the dynamic cycle time of the product’s step is applied to estimate the arrival time of the work in process (WIP) in front of machine. Furthermore, in order to avoid violating the time constraint of the WIP, an algorithm to calculate the latest time of the WIP to process on the machine is developed. Based on the latest process time of the WIP and the combination efficiency table, the production schedule of the cluster tools can be re-arranged to fulfill the production goal. The scheduling process will be renewed every three hours to make sure of the effectiveness and good performance of the schedule.

scholarly journals Signal and echo arrival‐time estimation using wavelets

1995 ◽  
Vol 97 (5) ◽  
pp. 3287-3287
Author(s):  
Phillip L. Ainsleigh
Keyword(s):  
Arrival Time ◽  
Time Estimation

scholarly journals Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models

2019 ◽  
Vol 64 (4) ◽  
pp. 045003 ◽  
Author(s):  
Alina L Bendinger ◽  
Charlotte Debus ◽  
Christin Glowa ◽  
Christian P Karger ◽  
Jörg Peter ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Arrival Time ◽  
Time Estimation ◽  
Small Animals ◽  
Resonance Imaging ◽  
Dynamic Contrast Enhanced ◽  
Spline Models ◽  
Contrast Enhanced ◽  
Bolus Arrival Time

scholarly journals Transit-Based Emergency Evacuation with Transit Signal Priority in Sudden-Onset Disaster

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Ciyun Lin ◽  
Bowen Gong
Keyword(s):  
Arrival Time ◽  
Time Estimation ◽  
Emergency Evacuation ◽  
Sudden Onset ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Transit Signal Priority ◽  
Signal Coordination ◽  
Arterial Traffic ◽  
Evacuation Route

This study presents methods of transit signal priority without transit-only lanes for a transit-based emergency evacuation in a sudden-onset disaster. Arterial priority signal coordination is optimized when a traffic signal control system provides priority signals for transit vehicles along an evacuation route. Transit signal priority is determined by “transit vehicle arrival time estimation,” “queuing vehicle dissipation time estimation,” “traffic signal status estimation,” “transit signal optimization,” and “arterial traffic signal coordination for transit vehicle in evacuation route.” It takes advantage of the large capacities of transit vehicles, reduces the evacuation time, and evacuates as many evacuees as possible. The proposed methods were tested on a simulation platform with Paramics V6.0. To evaluate and compare the performance of transit signal priority, three scenarios were simulated in the simulator. The results indicate that the methods of this study can reduce the travel times of transit vehicles along an evacuation route by 13% and 10%, improve the standard deviation of travel time by 16% and 46%, and decrease the average person delay at a signalized intersection by 22% and 17% when the traffic flow saturation along an evacuation route is0.8<V/C≤1.0andV/C>1.0, respectively.

scholarly journals Arrival Time Estimation for Bus Information System Using Hidden Markov Model

2017 ◽  
Vol 6 (4) ◽  
pp. 189-196
Author(s):  
Chul Young Park ◽  
Hong Geun Kim ◽  
Chang Sun Shin ◽  
Yong Yun Cho ◽  
Jang Woo Park
Keyword(s):  
Information System ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Arrival Time ◽  
Hidden Markov ◽  
Time Estimation
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