FORM OF "GANGI" AND SNOW REMOVING OF PUBLIC HOUSING IN HOKKAIDO AND AOMORI : Study on the common space design of apartment houses in snowy regions Part 1

The present article explores the collective imaginary of the cenacle, referring to the case of Viața românească literary group from Iași, focussing on the bodily community and its representations in the common space, understood as space-in-common. This approach shifts the interest from the ideological component that is the ‘poporanism’, as promoted by Viața românească revue, to the ethical and social aspects of the community. This does not mean that the bodily community is “more real” than the ideological community, or that it translates with fidelity the common practices of the cenacle; the bodily community is in fact another form of representation, a phantasm of the living-together, analysed through Roland Barthes’s theory as the space where solitude and sociability coexist. The corporal representations of the community, always engaged in an ethical debate, is further discussed through two manners of the living-together: the gesture and the rhythm. The theoretical reference of this analysis is Marielle Macéʼs book Styles. Critique de nos formes de vie, which proposes a formal approach of life, concentrating on the ethical implications. The issues derived from this sort of reading state the relation between the body and the environment, the vicinities and the somatic interactions between the members of the cenacle, the adjustment of distances, and the maintenance of solitude inside the community. The gestures, attitudes, behaviour, verbal and non-verbal tics, clothing, the manners of speech or the rhythm of doing certain things are seen not as marks of personal identity that positions itself inside the spaces of power, but as collective signs, as form of encounter and interaction, of exposure to the others but also responsiveness of the others, of expropriation as well as appropriation, of affirmation as well as alteration of the forms of life.

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Analytical Comparison of Two Emotion Classification Models Based on Convolutional Neural Networks

Complexity ◽

10.1155/2021/6625141 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Huiping Jiang ◽

Demeng Wu ◽

Rui Jiao ◽

Zongnan Wang

Keyword(s):

Wavelet Transform ◽

Classification Accuracy ◽

Eeg Signal ◽

Classification Models ◽

Emotion Classification ◽

Common Space ◽

Average Classification Accuracy ◽

The Common ◽

The Brain

Electroencephalography (EEG) is the measurement of neuronal activity in different areas of the brain through the use of electrodes. As EEG signal technology has matured over the years, it has been applied in various methods to EEG emotion recognition, most significantly including the use of convolutional neural network (CNN). However, these methods are still not ideal, and shortcomings have been found in the results of some models of EEG feature extraction and classification. In this study, two CNN models were selected for the extraction and classification of preprocessed data, namely, common spatial patterns- (CSP-) CNN and wavelet transform- (WT-) CNN. Using the CSP-CNN, we first used the common space model to reduce dimensionality and then applied the CNN directly to extract and classify the features of the EEG; while, with the WT-CNN model, we used the wavelet transform to extract EEG features, thereafter applying the CNN for classification. The EEG classification results of these two classification models were subsequently analyzed and compared, with the average classification accuracy of the CSP-CNN model found to be 80.56%, and the average classification accuracy of the WT-CNN model measured to 86.90%. Thus, the findings of this study show that the average classification accuracy of the WT-CNN model was 6.34% higher than that of the CSP-CNN.

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