Discourse and time in Shakespeare’s Romeo and Juliet

1999 ◽  
Vol 8 (2) ◽  
pp. 143-161 ◽  
Author(s):  
Vimala Herman

This article explores different verbal resources for the representation of time in drama. Drama as a genre is subjected to different pressures of time, given that the fictional time spans in the dramatic world must be realized within the real time allocated to a performance, a context which a dramatic text necessarily addresses. The temporal scope of plays can be highly expanded or contracted, but whatever option is used in a play, it is the result of the strategic exploitation of different resources. Theatre provides non-verbal means, like lighting and décor, but verbal resources are more dynamic. The verbal dialogue enacts speech events, and speech events are tied to spatio-temporal contexts, which can be transformed via speech use. The article examines various verbal resources like deixis, tense and aspect, lexical choices in clock and calendrical references, and pragmatics in order to explore their productive functions in constructing the complex and dynamic temporal world of one play, Shakespeare’s Romeo and Juliet.

Author(s):  
Tongwen Li ◽  
Chengyue Zhang ◽  
Huanfeng Shen ◽  
Qiangqiang Yuan ◽  
Liangpei Zhang

Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM<sub>2.5</sub>. However, the satellite-based monitoring of ground-level PM<sub>2.5</sub> is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM<sub>2.5</sub> in real time. Second, many data gaps exist in satellitederived PM<sub>2.5</sub> due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM<sub>2.5</sub> in a deep learning architecture. On this basis, the satellite-derived PM<sub>2.5</sub> in conjunction with ground PM<sub>2.5</sub> measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM<sub>2.5</sub> distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R<sup>2</sup>&amp;thinsp;=&amp;thinsp;0.80, RMSE&amp;thinsp;=&amp;thinsp;17.49&amp;thinsp;&amp;mu;g/m<sup>3</sup>) for the estimation of PM<sub>2.5</sub>. The missing data in satellite-derive PM<sub>2.5</sub> are accurately recovered, with R<sup>2</sup> between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM<sub>2.5</sub>.


2014 ◽  
Author(s):  
Irving Biederman ◽  
Ori Amir
Keyword(s):  

2020 ◽  
Vol 82 ◽  
pp. 149-160
Author(s):  
N Kargapolova

Numerical models of the heat index time series and spatio-temporal fields can be used for a variety of purposes, from the study of the dynamics of heat waves to projections of the influence of future climate on humans. To conduct these studies one must have efficient numerical models that successfully reproduce key features of the real weather processes. In this study, 2 numerical stochastic models of the spatio-temporal non-Gaussian field of the average daily heat index (ADHI) are considered. The field is simulated on an irregular grid determined by the location of weather stations. The first model is based on the method of the inverse distribution function. The second model is constructed using the normalization method. Real data collected at weather stations located in southern Russia are used to both determine the input parameters and to verify the proposed models. It is shown that the first model reproduces the properties of the real field of the ADHI more precisely compared to the second one, but the numerical implementation of the first model is significantly more time consuming. In the future, it is intended to transform the models presented to a numerical model of the conditional spatio-temporal field of the ADHI defined on a dense spatio-temporal grid and to use the model constructed for the stochastic forecasting of the heat index.


2015 ◽  
Vol 2 (1) ◽  
pp. 35-41
Author(s):  
Rivan Risdaryanto ◽  
Houtman P. Siregar ◽  
Dedy Loebis

The real-time system is now used on many fields, such as telecommunication, military, information system, evenmedical to get information quickly, on time and accurate. Needless to say, a real-time system will always considerthe performance time. In our application, we define the time target/deadline, so that the system should execute thewhole tasks under predefined deadline. However, if the system failed to finish the tasks, it will lead to fatal failure.In other words, if the system cannot be executed on time, it will affect the subsequent tasks. In this paper, wepropose a real-time system for sending data to find effectiveness and efficiency. Sending data process will beconstructed in MATLAB and sending data process has a time target as when data will send.


Author(s):  
Jiyang Yu ◽  
Dan Huang ◽  
Siyang Zhao ◽  
Nan Pei ◽  
Huixia Cheng ◽  
...  

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