Comparative Study with Fuzzy Entropy and Similarity Measure: One-to-One Correspondence

Soft set, as a parametrized family of subsets of a crisp universal set, has more ability to handle uncertain information. In this paper, we propose two types of similarity measure between soft sets and made a comparative study of these two techniques. Also we have shown an application of this similarity measure of soft sets.

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A descriptive comparative study of the strategies applied for the translation of the vernacular dialect of John Steinbeck’s Of Mice and Men as a sociolect into Farsi

Babel ◽

10.1075/babel.00105.ala ◽

2019 ◽

Vol 65 (4) ◽

pp. 538-561

Author(s):

Mahsa Ala ◽

Farzad Salahshoor

Keyword(s):

Comparative Study ◽

The Novel ◽

Standard Language ◽

Of Mice And Men ◽

One To One ◽

Chicano English ◽

The Way

Abstract This study aims to identify and compare the strategies applied by native Farsi Translators, Parviz Dariyush (1975) and Soroush Habibi (2009), in rendering the vernacular dialect (Chicano English) of John Steinbeck’s Of Mice and Men (1965) as a sociolect into Farsi. One hundred samples which contained seven unique characteristics of vernacular dialect limited to the two main characters of the novel, George and Lennie, were extracted from the novel with their Farsi equivalents. Sienkiewicz (1984, as cited in Berezowski 1997: 35) proposed strategies for the translation of dialects are taken as the model for this study to investigate the way dialectal features are dealt with in the selected parts and to check whether the procedure proposed by Sienkiewicz is sufficient and adequate for their translation. Analysing these samples, the results showed that one-to-one transference of dialectal elements is not practically possible into Farsi. However, both translators used phonological, syntactical, and morphological irregularities of Colloquial Farsi to show that the language of the novel is not standard language. Approximate Variety Substitution is the most frequent strategy used by Habibi and Dariyush. The aim of this strategy is to select a colloquial variety that has some dialectal features such as lexical, phonological, and morphological specifics and at the same time does not present an obvious recognizable TL dialect.

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Comparative Study of Fuzzy Entropy with Relative Spike Amplitude Features for Recognizing Wake-Sleep Stage 1 EEGs

International Journal of Biomedical and Clinical Engineering ◽

10.4018/ijbce.2015070102 ◽

2015 ◽

Vol 4 (2) ◽

pp. 12-25 ◽

Cited By ~ 1

Author(s):

Natarajan Sriraam ◽

B. R. Purnima ◽

Uma Maheswari Krishnaswamy

Keyword(s):

Comparative Study ◽

Sleep Stage ◽

Research Work ◽

Fuzzy Entropy ◽

Elman Neural Network ◽

Gold Standard Method ◽

Spike Amplitude ◽

Stage 1 ◽

Two Stages ◽

Stage Analysis

Electroencephalogram (EEG) based sleep stage analysis considered to be the gold standard method for assessment of sleep architecture. Of importance, transition between the first two stages, wake-sleep stage 1 found to be reliable quantitative tool for drowsiness and fatigue detection. The selection of appropriate feature pattern for EEGs is a quite challenging task due to its non-linear and non-stationary nature of the EEG signals. This research work attempts to provide a comparative study of time influence of time domain feature, relative spike amplitude (RSA) with entropy feature, fuzzy entropy(FE) for recognizing the transition between wake and sleep stage 1. EEGs extracted from offline polysomnography database is used and the extracted RSA and FE wake-sleep stage 1 derived EEG features are further classified using a feedback recurrent Elman neural network (REN) classifier. EEGs are segmented into 1s pattern. Simulation of the REN classifier revealed that the FE feature with REN yields a CA of 99.6% compared to that of with RSA feature.

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