Deep EM Method for Proactively Prediction of Resistivity ahead of Bit to Determine Salt Bottom Position

2020 ◽  
Author(s):  
Qing Bin Guo ◽  
Xiang Bao Hao ◽  
Chao Wu ◽  
Jean Seydoux ◽  
Chao Wang ◽  
...  
Keyword(s):  
Bottom Position ◽  
Em Method

Deep EM Method for Proactively Prediction of Resistivity ahead of Bit to Determine Salt Bottom Position

2020 ◽  
Author(s):  
Qing Bin Guo ◽  
Xiang Bao Hao ◽  
Chao Wu ◽  
Jean Seydoux ◽  
Chao Wang ◽  
...  
Keyword(s):  
Bottom Position ◽  
Em Method

Mapping of subsurface fault structures by VLF-EM method in Al Khoud area, Muscat, Sultanate of Oman

2016 ◽  
Vol 9 (5) ◽  
Author(s):  
Abdullah Mubarak Al Bulushi ◽  
Mohammed Al Wardi ◽  
Bader Al Shaqsi ◽  
N. Sundararajan
Keyword(s):  
Sultanate Of Oman ◽  
Em Method ◽  
Fault Structures

An In Vivo Method to Study Mouse Blood-Testis Barrier Integrity

10.3791/58512 ◽  
2018 ◽  
Author(s):  
Mengrou Liu ◽  
Chunsen Zhu ◽  
Shun Bai ◽  
Xin Li ◽  
Kaiqiang Fu ◽  
...  
Keyword(s):  
Mouse Blood ◽  
Barrier Integrity ◽  
Em Method ◽  
Blood Testis Barrier

scholarly journals An In Vivo Method for Evaluating the Gut-Blood Barrier and Liver Metabolism of Microbiota Products

10.3791/58456 ◽  
2018 ◽  
Author(s):  
Kinga Jaworska ◽  
Tomasz Huc ◽  
Marta Gawrys ◽  
Maksymilian Onyszkiewicz ◽  
Emilia Samborowska ◽  
...  
Keyword(s):  
Liver Metabolism ◽  
Em Method

scholarly journals In Vitro Method to Control Concentrations of Halogenated Gases in Cultured Alveolar Epithelial Cells

10.3791/58554 ◽  
2018 ◽  
Author(s):  
Raïko Blondonnet ◽  
Bertille Paquette ◽  
Damien Richard ◽  
Rémi Bourg ◽  
Géraldine Laplace ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Alveolar Epithelial Cells ◽  
Alveolar Epithelial ◽  
Em Method

scholarly journals Analysis of Decision Making Process in Moneyball: The Art of Winning an Unfair Game

The Winners ◽  
2015 ◽  
Vol 16 (1) ◽  
pp. 57
Author(s):  
Mochamad Sandy Triady ◽  
Ami Fitri Utami
Keyword(s):  
Decision Making ◽  
Excellent Result ◽  
Data Driven ◽  
Decision Making Process ◽  
Data Driven Decision Making ◽  
General Manager ◽  
Use Of Data ◽  
Bottom Position ◽  
Using Data ◽  
Baseball Team

Billy Beanes’s success in using data-driven decision making in baseball industry is wonderfully written by Michael Lewis in Moneyball. As a general manager in baseball team that were in the bottom position of the league from the financial side to acquire the players, Beane, along with his partner, explored the use of data in choosing the team’s player. They figured out how to determine the worth of every player.The process was not smooth, due to the condition of baseball industry that was not common with using advanced statistic in acquiring   players. Many teams still use the old paradigm that rely on experts’ judgments, intuition, or experience in decision making process. Moneyball approached that using data-driven decision making gave excellent result for Beane’s team. The team won 20 gamessequently in the 2002 season and also spent the lowest cost per win than other teams.This paper attempts to review the principles of Moneyball – The Art of Winning an Unfair Game as a process of decision making and gives what we can learn from the story in order to win the games, the unfair games.

Bayesian analysis of capture-recapture model and diagnostic test in clinical trials

2014 ◽  
Author(s):  
◽  
Dan Zheng
Keyword(s):  
Clinical Trials ◽  
Simulation Study ◽  
Behavioral Response ◽  
Bayesian Method ◽  
Original Method ◽  
Potential Bias ◽  
The Em Algorithm ◽  
Em Method ◽  
Capture Recapture ◽  
Simulation Results

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Capture-recapture models have been widely used to estimate the size of a target wildlife population. There are three major sources of variations that can affect capture probabilities: time (i.e., capture probabilities vary with time or trapping occasion), behavioral response (i.e., capture probabilities vary due to a trap response of animals to the first capture), and heterogeneity (i.e., capture probabilities vary by individual animal). There are eight models regarding possible combinations of these factors, including M0, Mt, Mb, Mh, Mtb, Mth, Mbh, and Mtbh. A capture-recapture model (Mb model) was created to present the behavioral response effect. The objective Bayesian analysis for the population size was developed and compared with common maximum likelihood estimates (MLEs). Simulation results demonstrate the advantages of the objective Bayesian over MLEs. Two real examples about a deer mouse are presented and one R package (OBMbpkg) was built for application. Companion diagnostics (CDx) for personalized medicine is commonly applied to in vitro diagnostic (IVD) industry and clinical trials for specific disease or treatment with biomarkers (e.g. molecular targets). The Bayesian method with Gibbs sampler was used to estimate the potential bias caused by imperfect CDx under the targeted design, where only patients with a positive diagnosis were enrolled the clinical trials. A simulation study was conducted to evaluate the performance of the Bayesian method and to compare with the EM algorithm. The Bayesian model selection method with G-prior was used to test treatment effects of targeted drugs for patients with biomarkers under the targeted design. A simulation study was conducted to evaluate the performance of the Bayesian method and to compare it with the original method and EM method when sample size is small. Eventually a biomarker-stratified design was studied, while patients enrolled in clinical trials could be divided into two groups (i.e., those with a positive or negative diagnosis). Both the EM algorithm and Bayesian method were used to estimate the potential bias caused by imperfect CDx. Simulation results demonstrate the advantages of the Bayesian method over the original method and EM method.

Sign in / Sign up

Export Citation Format

Share Document