scholarly journals VR-Fit: Walking-in-Place Locomotion with Real Time Step Detection for VR-Enabled Exercise

2019 ◽  
pp. 255-266
Author(s):  
Sercan Sari ◽  
Ayse Kucukyilmaz
Keyword(s):  
Real Time ◽  
Time Step ◽  
Step Detection

Virtual proprioception with real-time step detection and processing

2008 ◽  
Author(s):  
Robert LeMoyne ◽  
Cristian Coroian ◽  
Timothy Mastroianni ◽  
Winston Wu ◽  
Warren Grundfest ◽  
...  
Keyword(s):  
Real Time ◽  
Time Step ◽  
Step Detection

scholarly journals Real-time, step-wise, electrical detection of protein molecules using dielectrophoretically aligned SWNT-film FET aptasensors

Lab on a Chip ◽  
2010 ◽  
Vol 10 (16) ◽  
pp. 2052 ◽  
Author(s):  
Taechang An ◽  
Ki Su Kim ◽  
Sei Kwang Hahn ◽  
Geunbae Lim
Keyword(s):  
Real Time ◽  
Electrical Detection ◽  
Time Step ◽  
Protein Molecules ◽  
Swnt Film

A Modular Code for Real Time Dynamic Simulation of Gas Turbines in Simulink

2002 ◽  
Vol 128 (3) ◽  
pp. 506-517 ◽  
Author(s):  
S. M. Camporeale ◽  
B. Fortunato ◽  
M. Mastrovito
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Gas Turbine ◽  
Dynamic Behavior ◽  
Gas Turbines ◽  
Simulation Software ◽  
Computational Time ◽  
High Fidelity ◽  
Time Step ◽  
The Mathematical Model

A high-fidelity real-time simulation code based on a lumped, nonlinear representation of gas turbine components is presented. The code is a general-purpose simulation software environment useful for setting up and testing control equipments. The mathematical model and the numerical procedure are specially developed in order to efficiently solve the set of algebraic and ordinary differential equations that describe the dynamic behavior of gas turbine engines. For high-fidelity purposes, the mathematical model takes into account the actual composition of the working gases and the variation of the specific heats with the temperature, including a stage-by-stage model of the air-cooled expansion. The paper presents the model and the adopted solver procedure. The code, developed in Matlab-Simulink using an object-oriented approach, is flexible and can be easily adapted to any kind of plant configuration. Simulation tests of the transients after load rejection have been carried out for a single-shaft heavy-duty gas turbine and a double-shaft aero-derivative industrial engine. Time plots of the main variables that describe the gas turbine dynamic behavior are shown and the results regarding the computational time per time step are discussed.

scholarly journals Be Relevant, Non-Redundant, and Timely: Deep Reinforcement Learning for Real-Time Event Summarization

2020 ◽  
Vol 34 (05) ◽  
pp. 9410-9417
Author(s):  
Min Yang ◽  
Chengming Li ◽  
Fei Sun ◽  
Zhou Zhao ◽  
Ying Shen ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Language Processing ◽  
Semantic Features ◽  
Unified Framework ◽  
Time Step ◽  
Dynamic Memory ◽  
The Arts ◽  
Real World Datasets ◽  
Event Summarization

Real-time event summarization is an essential task in natural language processing and information retrieval areas. Despite the progress of previous work, generating relevant, non-redundant, and timely event summaries remains challenging in practice. In this paper, we propose a Deep Reinforcement learning framework for real-time Event Summarization (DRES), which shows promising performance for resolving all three challenges (i.e., relevance, non-redundancy, timeliness) in a unified framework. Specifically, we (i) devise a hierarchical cross-attention network with intra- and inter-document attentions to integrate important semantic features within and between the query and input document for better text matching. In addition, relevance prediction is leveraged as an auxiliary task to strengthen the document modeling and help to extract relevant documents; (ii) propose a multi-topic dynamic memory network to capture the sequential patterns of different topics belonging to the event of interest and temporally memorize the input facts from the evolving document stream, avoiding extracting redundant information at each time step; (iii) consider both historical dependencies and future uncertainty of the document stream for generating relevant and timely summaries by exploiting the reinforcement learning technique. Experimental results on two real-world datasets have demonstrated the advantages of DRES model with significant improvement in generating relevant, non-redundant, and timely event summaries against the state-of-the-arts.

scholarly journals A model tool for assessing real-time mixing of mineral and anthropogenic pollutants in East Asia: a case study of April 2005

2008 ◽  
Vol 8 (13) ◽  
pp. 3603-3622 ◽  
Author(s):  
F. Lasserre ◽  
G. Cautenet ◽  
C. Bouet ◽  
X. Dong ◽  
Y. J. Kim ◽  
...  
Keyword(s):  
East Asia ◽  
Real Time ◽  
Anthropogenic Pollution ◽  
Atmospheric Modeling ◽  
Time Step ◽  
Anthropogenic Pollutants ◽  
Vertical Distributions ◽  
Dust Events ◽  
Horizontal And Vertical Distributions

Abstract. In order to assess the complex mixing of atmospheric anthropogenic and natural pollutants over the East Asian region, we present a modelling tool which takes into account the main aerosols which are to be found simultaneously over China, Korea and Japan during springtime. Using the mesoscale RAMS (Regional Atmospheric Modeling System) tool, we present a simulation of natural (desert) dust events along with some of the most critical anthropogenic pollutants over East Asia, sulphur elements (SO2 and SO2-4) and Black Carbon (BC). As regards a one-week case study of dust events which occurred during late April 2005 over an area extending from the Gobi deserts to the Japan surroundings, we satisfactorily model the behaviours of the different aerosol plumes. We focus on possible dust mixing with the anthropogenic pollutants from megacities. For both natural and anthropogenic pollution, the model results are in fairly good agreement with the horizontal and vertical distributions of concentrations as measured by in situ LIDAR, and as observed in remote data, PM10 data and literature. In particular, we show that a simplified chemistry approach of this complex issue is sufficient to model this event, with a real-time step of 3 h. The model reproduces the main patterns and orders of magnitude for Aerosol Optical Thickness (AOT) and species contributions (via the Angström Exponent) when compared with the AErosol RObotic NETwork (AERONET) data.

Research on Modular Modeling Method of Reactor Coolant System Based on THEATRe

2014 ◽  
Author(s):  
Bo Shi ◽  
Zhao-Fei Tian
Keyword(s):  
Real Time ◽  
Data Exchange ◽  
Reactor Core ◽  
Simulation Software ◽  
Modeling Method ◽  
Time Step ◽  
Coolant Pump ◽  
Modular Modeling ◽  
Reactor Coolant ◽  
Coolant System

At present, research on the reactor coolant system is less yet, though modular modeling method has been widely used in the second-loop system of reactor. This paper takes the reactor coolant system of Qinshan-1 nuclear power plant as the object of study, analyses and researches on modular modeling method of reactor coolant system based on THEATRe, which is a large Thermal-Hydraulic real time simulation software developed by GSE Company and adopts NMNP (Nodal Momentum Nodal Pressure) solving method. This research establishes the modular model of the reactor coolant system equipments (including reactor core, main coolant pump, pressurizer, steam generator) using the THEATRe code. Due to each module is wrote into through different input cards, they can be solved by using their own matrix of velocity-pressure to guarantee the independence of the numerical calculation for different modular modules. THEATRe code does not have its own TDV like relap-5, meanwhile it also needs to ensure the pressurizer module can play a role in the multi-pressure node system. So this paper modifies solving method of the THEATRe source code to get suitable pressure boundary and flux boundary for RCS equipment modular module, and selects reasonable time step and data exchange frequency to achieve the data exchange of boundary pressure, flux and enthalpy among the equipment modules, which lays the foundation of establishing the real-time modular simulation model of the reactor coolant system in the future.

Real-Time Estimation of Directional Wave Spectra Using Non-Stationary Ship Motion Data

2009 ◽  
Author(s):  
Toshio Iseki
Keyword(s):  
Stochastic Processes ◽  
Real Time ◽  
Time Estimation ◽  
Ship Motion ◽  
Wave Spectra ◽  
Time Step ◽  
Motion Data ◽  
Stationary Stochastic Processes ◽  
Real Time Estimation ◽  
Directional Wave

The Bayesian modeling procedure is modified for real-time estimation of directional wave spectra using non-stationary ship motion data. The assumption of stationary stochastic processes is applied to the seaway, but not to ship response because it also depends on ship maneuvers. Ship response is strongly affected by changes in the encounter angle and frequency of waves. Therefore, it is need to be a real-time algorithm that can deal with non-stationary stochastic processes and estimate the directional wave spectra. In the proposed algorithm, the iterative calculations of the non-linear equations were optimized and the convergence was not achieved at every time step, but was achieved gradually over several time steps. In order to examine the reliability of the proposed method, real-time estimation was conducted by using the data of onboard experiments. Comparisons between the results of the proposed algorithm and a wave monitoring radar system show good agreements.

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