scholarly journals Parallel corpora. A real-time approach to the study of language change in progress

Diacronia ◽  
2015 ◽  
Author(s):  
Christian Mair
Keyword(s):  
Structural Change ◽  
Real Time ◽  
Language Change ◽  
Standard English ◽  
Short Term ◽  
Stylistic Variation ◽  
Linguistic Development ◽  
Parallel Corpora ◽  
Diachronic Change

The paper draws data from four matching one-million word corpora, namely Brown (US, 1961), LOB (GB, 1961), Frown (US, 1992) and FLOB (GB, 1991), in order to provide an integrated description of synchronic (regional and stylistic) variation and short-term diachronic change in written Standard English. The analysis of a fairly large number of morphosyntactic variables shows that instances of direct structural change are rather rare in the period under review. Nevertheless there are numerous statistically significant diachronic developments which, taken together, provide evidence for a coherent discourse-pragmatic trend, the ‘colloquialisation’ of the norms of written English. This linguistic development is argued to be driven by a more general sociocultural trend, the shift of public taste towards greater informality.

The sociolinguistics of a short-lived innovation: Tracing the development of quotative all across spoken and internet newsgroup data

2010 ◽  
Vol 22 (2) ◽  
pp. 191-219 ◽  
Author(s):  
Isabelle Buchstaller ◽  
John R. Rickford ◽  
Elizabeth Closs Traugott ◽  
Thomas Wasow ◽  
Arnold Zwicky
Keyword(s):  
Real Time ◽  
Language Change ◽  
Linguistic Variation ◽  
Research Projects ◽  
Short Term ◽  
The Past ◽  
History Of ◽  
Quantitative Analyses

AbstractThis paper examines a short-lived innovation, quotative all, in real and apparent time. We used a two-pronged method to trace the trajectory of all over the past two decades: (i) Quantitative analyses of the quotative system of young Californians from different decades; this reveals a startling crossover pattern: in 1990/1994, all predominates, but by 2005, it has given way to like. (ii) Searches of Internet newsgroups; these confirm that after rising briskly in the 1990s, all is declining. Tracing the changing usage of quotative options provides year-to-year evidence that all has recently given way to like. Our paper has two aims: We provide insights from ongoing language change regarding short-term innovations in the history of English. We also discuss our collaboration with Google Inc. and argue for the value of newsgroups to research projects investigating linguistic variation and change in real time, especially where recorded conversational tokens are relatively sparse.

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

Nowcasting global trade in goods and services

2020 ◽  
pp. 1-19
Author(s):  
Fernando Cantú-Bazaldúa
Keyword(s):  
Real Time ◽  
Relevant Information ◽  
Global Trade ◽  
Dynamic Factor ◽  
Timely Manner ◽  
Short Term ◽  
Dynamic Factor Models ◽  
Significant Information ◽  
Goods And Services ◽  
World Economic

World economic aggregates are compiled infrequently and released after considerable lags. There are, however, many potentially relevant series released in a timely manner and at a higher frequency that could provide significant information about the evolution of global aggregates. The challenge is then to extract the relevant information from this multitude of indicators and combine it to track the real-time evolution of the target variables. We develop a methodology based on dynamic factor models adapted for variables with heterogeneous frequencies, ragged ends and missing data. We apply this methodology to nowcast global trade in goods in goods and services. In addition to monitoring these variables in real time, this method can also be used to obtain short-term forecasts based on the most up-to-date values of the underlying indicators.

scholarly journals THE VALUE OF ROBUST STATISTICAL FORECASTS IN THE COVID-19 PANDEMIC

2021 ◽  
Vol 256 ◽  
pp. 19-43
Author(s):  
Jennifer L. Castle ◽  
Jurgen A. Doornik ◽  
David F. Hendry
Keyword(s):  
Structural Change ◽  
Measurement Errors ◽  
Epidemiological Models ◽  
Short Term ◽  
Data Measurement ◽  
Policy Interventions ◽  
Changing Trends ◽  
Technological Advances ◽  
The Difference ◽  
The Uk

The Covid-19 pandemic has put forecasting under the spotlight, pitting epidemiological models against extrapolative time-series devices. We have been producing real-time short-term forecasts of confirmed cases and deaths using robust statistical models since 20 March 2020. The forecasts are adaptive to abrupt structural change, a major feature of the pandemic data due to data measurement errors, definitional and testing changes, policy interventions, technological advances and rapidly changing trends. The pandemic has also led to abrupt structural change in macroeconomic outcomes. Using the same methods, we forecast aggregate UK unemployment over the pandemic. The forecasts rapidly adapt to the employment policies implemented when the UK entered the first lockdown. The difference between our statistical and theory based forecasts provides a measure of the effect of furlough policies on stabilising unemployment, establishing useful scenarios had furlough policies not been implemented.

Forecasting Model of Short-Term Traffic Flow Based on Cloud Model

2011 ◽  
Vol 94-96 ◽  
pp. 38-42
Author(s):  
Qin Liu ◽  
Jian Min Xu
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
Cloud Model ◽  
Prediction Method ◽  
Absolute Error ◽  
Short Term ◽  
Guangzhou City ◽  
Time Prediction ◽  
Real Time Traffic ◽  
Absolute Percent Error

In order to improve the prediction precision of the short-term traffic flow, a prediction method of short-term traffic flow based on cloud model was proposed. The traffic flow was fit by cloud model. The history cloud and the present cloud were built by historical traffic flow and present traffic flow. The forecast cloud is produced by both clouds. Then, combining with the volume of the short-term traffic flow of an intersection in Guangzhou City, the model was calculated and simulated through programming. Max Absolute Error (MAE) and Mean Absolute percent Error (MAPE) were used to estimate the effect of prediction. The simulation results indicate that this prediction method is effective and advanced. The change of the historical and real time traffic flow is taken into account in this method. Because the short-term traffic flow is dealt with as a whole, the error of prediction is avoided. The prediction precision and real-time prediction are satisfied.

scholarly journals Time- and Dose-Dependent Effects of 17 Beta-Estradiol on Short-Term, Real-Time Proliferation and Gene Expression in Porcine Granulosa Cells

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Sylwia Ciesiółka ◽  
Joanna Budna ◽  
Karol Jopek ◽  
Artur Bryja ◽  
Wiesława Kranc ◽  
...  
Keyword(s):  
Real Time ◽  
Granulosa Cells ◽  
Hormone Receptor ◽  
Proliferative Activity ◽  
Cell Transformation ◽  
Luteinizing Hormone Receptor ◽  
Luteal Cell ◽  
Ovarian Activity ◽  
Short Term

The key mechanisms responsible for achievement of full reproductive and developmental capability in mammals are the differentiation and transformation of granulosa cells (GCs) during folliculogenesis, oogenesis, and oocyte maturation. Although the role of 17 beta-estradiol (E2) in ovarian activity is widely known, its effect on proliferative capacity, gap junction connection (GJC) formation, and GCs-luteal cells transformation requires further research. Therefore, the goal of this study was to assess the real-time proliferative activity of porcine GCs in vitro in relation to connexin (Cx), luteinizing hormone receptor (LHR), follicle stimulating hormone receptor (FSHR), and aromatase (CYP19A1) expression during short-term (168 h) primary culture. The cultured GCs were exposed to acute (at 96 h of culture) and/or prolonged (between 0 and 168 h of culture) administration of 1.8 and 3.6 μM E2. The relative abundance of Cx36, Cx37, Cx40, Cx43, LHR, FSHR, and CYP19A1 mRNA was measured. We conclude that the proliferation capability of GCs in vitro is substantially associated with expression of Cxs, LHR, FSHR, and CYP19A1. Furthermore, the GC-luteal cell transformation in vitro may be significantly accompanied by the proliferative activity of GCs in pigs.

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