A risk estimation method of railway embankment collapse due to heavy rainfall

1994 ◽  
Vol 14 (1-2) ◽  
pp. 131-150 ◽  
Author(s):  
Katsuya Okada ◽  
Tomoyasu Sugiyama
Keyword(s):  
Heavy Rainfall ◽  
Risk Estimation ◽  
Estimation Method

scholarly journals Developing a control framework for self-adjusting prosthetic sockets incorporating tissue injury risk estimation and Generalized Predictive Control

2021 ◽  
Author(s):  
Florence M Mbithi ◽  
Joshua Steer ◽  
Andrew J Chipperfield ◽  
Alexander Dickinson
Keyword(s):  
Predictive Control ◽  
Lower Limb ◽  
Injury Risk ◽  
Tissue Injury ◽  
Risk Estimation ◽  
Soft Tissue Injury ◽  
Estimation Method ◽  
Generalized Predictive Control ◽  
Prosthetic Socket ◽  
Interfacial Pressure

Purpose: To perform activities of daily living (ADL), people with lower limb amputation depend on the prosthetic socket for stability and proprioceptive feedback. Poorly fitting sockets can cause discomfort, pain, limb tissue injuries, limited device usage, and potential rejection. Semi-passively controlled adjustable socket technologies exist, but these depend upon the user’s perception to determine safe interfacial pressure levels. This paper presents a framework for automatic control of an adjustable transtibial prosthetic socket that enables active adaptation of residuum-socket interfacial loading through localized actuators, based on soft tissue injury risk estimation. Method: Using finite element analysis, local interfacial pressure vs. compressive tissue strain relationships were estimated for three anatomical actuator locations, for tissue injury risk assessment within a control structure. Generalized Predictive Control of multiple actuators was implemented to maintain interfacial pressure within estimated safe and functional limits. Results: Controller simulation predicted satisfactory dynamic performance in several scenarios, based on previous related studies. Actuation rates of 0.06 – 1.51kPa/s with 0.67% maximum overshoot, and 0.75 – 1.58kPa/s were estimated for continuous walking, and for a demonstrative loading sequence of ADL, respectively. Conclusion: The developed platform could be useful for extending recent efforts in adjustable lower limb prosthetic socket design, particularly for individuals with residuum sensory impairment.

Modified UCT Algorithm with Risk Dominance Methods in Imperfect Information Game

2014 ◽  
Vol 610 ◽  
pp. 367-376 ◽  
Author(s):  
Jia Jia Zhang ◽  
Xuan Wang ◽  
Lin Yao ◽  
Jing Peng Li ◽  
Xue Dong Shen
Keyword(s):  
Risk Factors ◽  
Imperfect Information ◽  
Risk Estimation ◽  
Estimation Method ◽  
Estimation Methods ◽  
Test Bed ◽  
Risk Dominance ◽  
Payoff Dominance ◽  
Game Equilibrium ◽  
Risk Algorithm

UCT (Upper confidential bounds on Trees) has been applied quite well as a selection approach in MCTS(Monte Carlo Tree Search) in imperfect information games like poker. By using risk dominance as complementary part of decision method besides payoff dominance, opponent strategies is better characterized as their risk factors, like bluff actions in Texas Hold’em Poker . In this paper, estimation method about the influence of risk factors on computing game equilibrium is provided. A novel algorithm, UCT-risk is proposed as modification about UCT algorithm basing on risk estimation methods. To verify the performance of new algorithm, Texas Hold’em, a popular test-bed for AI research is chosen as the experiment platform. The Agent adopted UCT-risk algorithm performs as well or better as the best previous approaches in experiments. And also it is applied in a poker agent named HITSZ_CS_13 in the 2013 AAAI Computer Poker Competition, which confirms the effectiveness of the UCT-risk provided in this paper.

scholarly journals Exploring Risks Transferred from Cloud-Based Information Systems: A Quantitative and Longitudinal Model

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3488 ◽  
Author(s):  
Wafa Bouaynaya ◽  
Hongbo Lyu ◽  
Zuopeng Zhang
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Information Systems ◽  
Internet Of Things ◽  
Risk Estimation ◽  
Estimation Method ◽  
Cyber Physical Systems ◽  
Longitudinal Model ◽  
Physical Systems ◽  
A Company

With the growing popularity of Internet of Things (IoT) and Cyber-Physical Systems (CPS), cloud- based systems have assumed a greater important role. However, there lacks formal approaches to modeling the risks transferred through information systems implemented in a cloud-based environment. This paper explores formal methods to quantify the risks associated with an information system and evaluate its variation throughout its implementation. Specifically, we study the risk variation through a quantitative and longitudinal model spanning from the launch of a cloud-based information systems project to its completion. In addition, we propose to redefine the risk estimation method to differentiate a mitigated risk from an unmitigated risk. This research makes valuable contributions by helping practitioners understand whether cloud computing presents a competitive advantage or a threat to the sustainability of a company.

scholarly journals Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Noah Lorincz-Comi ◽  
Xiaofeng Zhu
Keyword(s):  
Pulse Pressure ◽  
Type Ii Diabetes ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Risk Estimation ◽  
Estimation Method ◽  
Large Sample Size ◽  
Sample Type ◽  
Type Ii ◽  
Causal Inferences

AbstractMany cardiometabolic conditions have demonstrated associative evidence with COVID-19 hospitalization risk. However, the observational designs of the studies in which these associations are observed preclude causal inferences of hospitalization risk. Mendelian Randomization (MR) is an alternative risk estimation method more robust to these limitations that allows for causal inferences. We applied four MR methods (MRMix, IMRP, IVW, MREgger) to publicly available GWAS summary statistics from European (COVID-19 GWAS n = 2956) and multi-ethnic populations (COVID-19 GWAS n = 10,908) to better understand extant causal associations between Type II Diabetes (GWAS n = 659,316), BMI (n = 681,275), diastolic and systolic blood pressure, and pulse pressure (n = 757,601 for each) and COVID-19 hospitalization risk across populations. Although no significant causal effect evidence was observed, our data suggested a trend of increasing hospitalization risk for Type II diabetes (IMRP OR, 95% CI 1.67, 0.96–2.92) and pulse pressure (OR, 95% CI 1.27, 0.97–1.66) in the multi-ethnic sample. Type II diabetes and Pulse pressure demonstrates a potential causal association with COVID-19 hospitalization risk, the proper treatment of which may work to reduce the risk of a severe COVID-19 illness requiring hospitalization. However, GWAS of COVID-19 with large sample size is warranted to confirm the causality.

scholarly journals HIV continuum of care: expanding scope beyond a cross-sectional view to include time analysis: a systematic review

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Georgia Vourli ◽  
Ioannis Katsarolis ◽  
Nikos Pantazis ◽  
Giota Touloumi
Keyword(s):  
Risk Estimation ◽  
Estimation Method ◽  
Continuum Of Care ◽  
Hiv Care ◽  
Cross Sectional ◽  
Effective Response ◽  
Factors Affecting ◽  
Modelling Studies ◽  
The Cross ◽  
Hiv Continuum Of Care

Abstract Introduction The continuum of care (CoC) model has been used to describe the main pillars of HIV care. This study aims to systematically review methods and elucidate gaps in the CoC analyses, especially in terms of the timing of the progression through steps, recognized nowadays as a critical parameter for an effective response to the epidemic. Methods A PubMed and EMBASE databases search up to December 2019 resulted in 1918 articles, of which 209 were included in this review; 84 studies presented in major HIV conferences were also included. Studies that did not provide explicit definitions, modelling studies and those reporting only on metrics for subpopulations or factors affecting a CoC stage were excluded. Included articles reported results on 1 to 6 CoC stages. Results Percentage treated and virally suppressed was reported in 78%, percentage diagnosed and retained in care in 58%, percentage linked to care in 54% and PLHIV in 36% of the articles. Information for all stages was provided in 23 studies. Only 6 articles use novel CoC estimates: One presents a dynamic CoC based on multistate analysis techniques, two base their time-to-next-stage estimates on a risk estimation method based on the cumulative incidence function, weighted for confounding and censoring and three studies estimated the HIV infection time based on mathematical modelling. Conclusion A limited number of studies provide elaborated time analyses of the CoC. Although time analyses lack the straightforward interpretation of the cross-sectional CoC, they provide valuable insights for the timely response to the HIV epidemic. A future goal would be to develop a model that retains the simplicity of the cross-sectional CoC but also incorporates timing between stages.

scholarly journals Cardiometabolic risks of SARS-CoV-2 hospitalization using Mendelian Randomization

2021 ◽  
Author(s):  
Noah J Lorincz-Comi ◽  
Xiaofeng Zhu
Keyword(s):  
Pulse Pressure ◽  
Type Ii Diabetes ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Risk Estimation ◽  
Estimation Method ◽  
Large Sample Size ◽  
Sample Type ◽  
Type Ii ◽  
Causal Inferences

Many cardiometabolic conditions have demonstrated associative evidence with COVID-19 hospitalization risk. However, the observational designs of the studies in which these associations are observed preclude causal inferences of hospitalization risk. Mendelian Randomization (MR) is an alternative risk estimation method more robust to these limitations that allows for causal inferences. We applied four MR methods (MRMix, IMRP, IVW, MREgger) to publicly available GWAS summary statistics from European (COVID-19 GWAS n=2,956) and multi-ethnic populations (COVID-19 GWAS n=10,808) to better understand extant causal associations between Type II Diabetes (GWAS n=659,316), BMI (n=681,275), diastolic and systolic blood pressure, and pulse pressure (n=757,601 for each) and COVID-19 hospitalization risk across populations. Although no significant causal effect evidence was observed, our data suggested a trend of increasing hospitalization risk for Type II diabetes (IMRP OR, 95% CI: 1.67, 0.96-2.92) and pulse pressure (OR, 95% CI: 1.27, 0.97-1.66) in the multi-ethnic sample. Type II diabetes and Pulse pressure demonstrates a potential causal association with COVID-19 hospitalization risk, the proper treatment of which may work to reduce the risk of a severe COVID-19 illness requiring hospitalization. However, GWAS of COVID-19 with large sample size is warranted to confirm the causality.

Assimilation Impact of Different GPS Analysis Methods on Precipitation Forecast: A Heavy Rainfall Case Study of Kani City, Gifu Prefecture on July 15, 2010

2017 ◽  
Vol 12 (5) ◽  
pp. 944-955
Author(s):  
Shingo Shimizu ◽  
Seiichi Shimada ◽  
Kazuhisa Tsuboki ◽  
◽  
◽  
...  
Keyword(s):  
Heavy Rainfall ◽  
Estimation Method ◽  
Precipitable Water ◽  
Precipitation Forecast ◽  
Simultaneous Estimation ◽  
Zenith Delay ◽  
Analysis Methods ◽  
Rainfall Forecast ◽  
Gifu Prefecture ◽  
Orbit Data

In this study, we examined variations in predicted precipitable water produced from different Global Positioning System (GPS) zenith delay methods, and assessed the corresponding difference in predicted rainfall after assimilating the obtained precipitable water data. Precipitable water data estimated from the GPS and three-dimensional horizontal wind velocity field derived from the X-band dual polarimetric radar were assimilated in CReSS and rainfall forecast experiments were conducted for the heavy rainfall system in Kani City, Gifu Prefecture on July 15, 2010. In the GPS analysis, a method to simultaneously estimate coordinates and zenith delay, i.e., the simultaneous estimation method, and a method to successively estimate coordinates and zenith delay, i.e., the successive estimation method, were used to estimate precipitable water. The differences generated from using predicted orbit data provided in pseudo-real time from the International GNSS (Global Navigation Satellite System) Service for geodynamics (IGS) versus precise orbit data released after a 10-day delay were examined. The change in precipitable water due to varying the analysis methods was larger than that due to the type of satellite orbit information. In the rainfall forecast experiments, those using the successive estimation method results had a better precision than those using the simultaneous estimation method results. Both methods that included data assimilation had higher rainfall forecast precisions than the forecast precision without precipitable water assimilation. Water vapor obtained from GPS analysis is accepted as important in rainfall forecasting, but the present study showed additional improvements can be attained from incorporating a zenith delay analysis method.

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