Measuring the Performance of a Location-Aware Text Prediction System

2015 ◽  
Vol 7 (1) ◽  
pp. 1-29 ◽  
Author(s):  
Luís Filipe Garcia ◽  
Luís Caldas De Oliveira ◽  
David Martins De Matos
Keyword(s):  
Prediction System ◽  
Location Aware ◽  
Text Prediction

A location-aware user tracking and prediction system

2009 ◽  
Author(s):  
I. Al Ridhawi ◽  
M. Aloqaily ◽  
A. Karmouch ◽  
N Agoulmine
Keyword(s):  
Prediction System ◽  
Location Aware

THE LANGUAGE COMPONENT OF THE FASTY TEXT PREDICTION SYSTEM

2005 ◽  
Vol 19 (8) ◽  
pp. 743-781 ◽  
Author(s):  
Harald Trost ◽  
Johannes Matiasek ◽  
Marco Baroni
Keyword(s):  
Prediction System ◽  
Text Prediction

scholarly journals An Approach for a Next-Word Prediction for Ukrainian Language

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Khrystyna Shakhovska ◽  
Iryna Dumyn ◽  
Natalia Kryvinska ◽  
Mohan Krishna Kagita
Keyword(s):  
Markov Chains ◽  
Hybrid Model ◽  
Prediction System ◽  
Text Generation ◽  
Word Prediction ◽  
Current Output ◽  
Prediction Task ◽  
Limited Support ◽  
Text Prediction ◽  
Sequential Nature

Text generation, in particular, next-word prediction, is convenient for users because it helps to type without errors and faster. Therefore, a personalized text prediction system is a vital analysis topic for all languages, primarily for Ukrainian, because of limited support for the Ukrainian language tools. LSTM and Markov chains and their hybrid were chosen for next-word prediction. Their sequential nature (current output depends on previous) helps to successfully cope with the next-word prediction task. The Markov chains presented the fastest and adequate results. The hybrid model presents adequate results but it works slowly. Using the model, user can generate not only one word but also a few or a sentence or several sentences, unlike T9.

Application of the Boundary Element Method and Modal Analysis to Tire Acoustics Problems

1993 ◽  
Vol 21 (2) ◽  
pp. 66-90 ◽  
Author(s):  
Y. Nakajima ◽  
Y. Inoue ◽  
H. Ogawa
Keyword(s):  
Finite Element ◽  
Boundary Element Method ◽  
Boundary Element ◽  
Acoustic Radiation ◽  
Traffic Noise ◽  
Noise Prediction ◽  
Prediction System ◽  
Tire Noise ◽  
Acoustic Contribution ◽  
Element Method

Abstract Road traffic noise needs to be reduced, because traffic volume is increasing every year. The noise generated from a tire is becoming one of the dominant sources in the total traffic noise because the engine noise is constantly being reduced by the vehicle manufacturers. Although the acoustic intensity measurement technology has been enhanced by the recent developments in digital measurement techniques, repetitive measurements are necessary to find effective ways for noise control. Hence, a simulation method to predict generated noise is required to replace the time-consuming experiments. The boundary element method (BEM) is applied to predict the acoustic radiation caused by the vibration of a tire sidewall and a tire noise prediction system is developed. The BEM requires the geometry and the modal characteristics of a tire which are provided by an experiment or the finite element method (FEM). Since the finite element procedure is applied to the prediction of modal characteristics in a tire noise prediction system, the acoustic pressure can be predicted without any measurements. Furthermore, the acoustic contribution analysis obtained from the post-processing of the predicted results is very helpful to know where and how the design change affects the acoustic radiation. The predictability of this system is verified by measurements and the acoustic contribution analysis is applied to tire noise control.

Short-Term Flood Prediction System

2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Konrad Nering
Keyword(s):  
Flash Floods ◽  
Prediction System ◽  
Short Term ◽  
Data Set ◽  
Flood Prediction ◽  
Full Operation

AbstractThis paper describes a fully functional short-term flood prediction system. Its effect has been tested on watershed of Lubieńka river in Małopolska. To use this system it must have a data set also described in this paper. A modification of the system to adopt for predicting flash floods was described. Full operation of the system is shown on example of real flood on Lubieńka river in June 2011.

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