From linear models of communications to network model - evolution and fusion

2018 ◽  
Vol 1 (3) ◽  
pp. 161-172
Author(s):  
Ramyl Karimov ◽  
Fachsprache ◽  
2019 ◽  
Vol 41 (S1) ◽  
pp. 4-22
Author(s):  
Larisa M. Alekseeva ◽  
Svetlana L. Mishlanova

Abstract The article focuses on the derivational perspective of metaphor studies. Derivation is regarded as a complex cognitive process, represented within speech activities. In this sense, derivation is viewed as a universal process of language units’ production according to the rules of text-formation. The basic feature of the derivational approach to the mechanism of metaphor is determined by the inner syntax, especially by the principle of contamination of two sentences – introductive and basic, which fulfill different functions. In this paper we shall present a theoretical account of metaphorisation as a universal derivational process controlled by means of such laws, as incorporation, contamination and compression. We take as basic the premise that metaphor is a more complicated process than it is described in traditional theories, since it is dependent on cognition and knowledge communication. In contrast to the traditional approaches, metaphor is regarded here as the result of combination of two pictures of the reality, referential and imaginative. We believe that derivatology generates a new knowledge about metaphor mechanism and metaphor modeling. Comparing to linear models of metaphor, the derivational model is considered to be a network model. The latest derivatological ideas about metaphor enrich the concept of metaphor taking into consideration that it has to be studied not in isolation, but within a broad frame of text, discourse, cognition and communication.


Author(s):  
Tayyab Raza Fraz ◽  
Samreen Fatima

Forecasting macroeconomic and financial data are always difficult task to the researchers. Various statisticaland econometrics techniques have been used to forecast these variables more accurately. Furthermore, in the presenceof structural break, linear models are failed to model and forecast. Therefore, this study examines the forecastingperformance of economic variables of G7 countries: France, Italy, Canada, Germany, Japan, United Kingdom andUnited States of America using non-linear autoregressive neural network (ARNN) model, linear auto regressive (AR)and Auto regressive integrated moving average model (ARIMA) models. The economic variables are inflation,exchange rate and Gross Domestic Product (GDP) growth for the period from 1970 to 2015. To measure theperformance of the considered model Root, Mean Square Error, Mean Absolute Error and Mean Absolute PercentageError are used. The results show that the forecasts from the non-linear neural network model are undoubtedly better ascompared to the AR and the Box–Jenkins ARIMA models.


1974 ◽  
Vol 3 (9) ◽  
pp. 893-897
Author(s):  
Gerald McWilliams ◽  
James Poirot†
Keyword(s):  

1991 ◽  
Vol 8 (1) ◽  
pp. 77-90
Author(s):  
W. Steven Demmy ◽  
Lawrence Briskin
Keyword(s):  

2020 ◽  
Vol 41 (2) ◽  
pp. 61-67
Author(s):  
Marko Tončić ◽  
Petra Anić

Abstract. This study aims to examine the effect of affect on satisfaction, both at the between- and the within-person level for momentary assessments. Affect is regarded as an important source of information for life satisfaction judgments. This affective effect on satisfaction is well established at the dispositional level, while at the within-person level it is heavily under-researched. This is true especially for momentary assessments. In this experience sampling study both mood and satisfaction scales were administered five times a day for 7 days via hand-held devices ( N = 74 with 2,122 assessments). Several hierarchical linear models were fitted to the data. Even though the amount of between-person variance was relatively low, both positive and negative affect had substantial effects on momentary satisfaction on the between- and the within-person level as well. The within-person effects of affect on satisfaction appear to be more pronounced than the between-person ones. At the momentary level, the amount of between-person variance is lower than in studies with longer time-frames. The affect-related effects on satisfaction possibly have a curvilinear relationship with the time-frame used, increasing in intensity up to a point and then decreasing again. Such a relationship suggests that, at the momentary level, satisfaction might behave in a more stochastic manner, allowing for transient events/data which are not necessarily affect-related to affect it.


1994 ◽  
Vol 39 (5) ◽  
pp. 475-476
Author(s):  
Paula L. Woehlke

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