This article focuses on the factors that influence the dynamics of the sociological imagination. The author argues for the codependence of sociological theorizing, thinking, and imagination that are analyzed through t...This article focuses on the factors that influence the dynamics of the sociological imagination. The author argues for the codependence of sociological theorizing, thinking, and imagination that are analyzed through the prism of the increasing complexity of social and cultural dynamics of the society, the accelerated complex development of human communities within the ＂arrow of time＂. He critically discusses the types of sociological imagination worked out by C. Wright Mills, P. Sztompka, S. Fuller, and U. Beck, and proposes his own model of sociological imagination in the form of a non-linear humanistic one that is based on the synthesis of social, hard and humane science. It deals with the acceleration of socio-cultural dynamics and glocal complexity, the integrity of the interdependent humanity, and synergetically takes into consideration paradoxical synthesis, breaks, risks, and dispersions of socium, its obiective, subjectively constructed, and virtual realities, searching for new forms of humanism, based on men＇s existential needs. It presupposes humane praxis--nowadays the world needs the passing over from technological to humane modernization that can be achieved due to a humanistic turn in sociology, its orientation on a non-linear humanistic sociological imagination.展开更多
Amharic folk literature is a time-honoured tradition dating back to the imperial songs of the 14th and 15th centuries. One of these subgenres is Amharic folk poetry which is permeated with the political, social, econo...Amharic folk literature is a time-honoured tradition dating back to the imperial songs of the 14th and 15th centuries. One of these subgenres is Amharic folk poetry which is permeated with the political, social, economic, and cultural legacies of successive Ethiopian governments that rise and demise. The image of these governments was determined by their integrity, vision, and responsiveness to the aspirations of the populace. This study was designed to determine the popular image of the imperial governments of Menelik II and Haile Selasse I as reflected in Amharic folk poetry. Without prejudice to some odes which invariably idealise the vision of these monarchs, the politically-inspired Amharic folk poetry is found to be critical of the feudal status quo thus perpetuating its negative images. This underpins the partial unpopularity of Menilik and Haile Selasse. However, these critical gestures would by no means undermine their monumental contributions to the reunification, modernization, and survival of Ethiopia. Thus, the contemporary Amharic folk-poetry is neither iconoclastic nor idealistic but an impassioned allegory of the nation-state.展开更多
Classifying single-trial electroencephalogram(EEG)based motor imagery(MI)tasks is extensively used to control brain-computer interface(BCI)applications,as a communication bridge between humans and computers.However,th...Classifying single-trial electroencephalogram(EEG)based motor imagery(MI)tasks is extensively used to control brain-computer interface(BCI)applications,as a communication bridge between humans and computers.However,the low signal-to-noise ratio and individual differences of EEG can affect the classification results negatively.In this paper,we propose an improved common spatial pattern(B-CSP)method to extract features for alleviating these adverse effects.First,for different subjects,the method of Bhattacharyya distance is used to select the optimal frequency band of each electrode including strong event-related desynchronization(ERD)and event-related synchronization(ERS)patterns;then the signals of the optimal frequency band are decomposed into spatial patterns,and the features that can describe the maximum differences of two classes of MI are extracted from the EEG data.The proposed method is applied to the public data set and experimental data set to extract features which are input into a back propagation neural network(BPNN)classifier to classify single-trial MI EEG.Another two conventional feature extraction methods,original common spatial pattern(CSP)and autoregressive(AR),are used for comparison.An improved classification performance for both data sets(public data set:91.25%±1.77%for left hand vs.foot and84.50%±5.42%for left hand vs.right hand;experimental data set:90.43%±4.26%for left hand vs.foot)verifies the advantages of the B-CSP method over conventional methods.The results demonstrate that our proposed B-CSP method can classify EEG-based MI tasks effectively,and this study provides practical and theoretical approaches to BCI applications.展开更多
文摘This article focuses on the factors that influence the dynamics of the sociological imagination. The author argues for the codependence of sociological theorizing, thinking, and imagination that are analyzed through the prism of the increasing complexity of social and cultural dynamics of the society, the accelerated complex development of human communities within the ＂arrow of time＂. He critically discusses the types of sociological imagination worked out by C. Wright Mills, P. Sztompka, S. Fuller, and U. Beck, and proposes his own model of sociological imagination in the form of a non-linear humanistic one that is based on the synthesis of social, hard and humane science. It deals with the acceleration of socio-cultural dynamics and glocal complexity, the integrity of the interdependent humanity, and synergetically takes into consideration paradoxical synthesis, breaks, risks, and dispersions of socium, its obiective, subjectively constructed, and virtual realities, searching for new forms of humanism, based on men＇s existential needs. It presupposes humane praxis--nowadays the world needs the passing over from technological to humane modernization that can be achieved due to a humanistic turn in sociology, its orientation on a non-linear humanistic sociological imagination.
文摘Amharic folk literature is a time-honoured tradition dating back to the imperial songs of the 14th and 15th centuries. One of these subgenres is Amharic folk poetry which is permeated with the political, social, economic, and cultural legacies of successive Ethiopian governments that rise and demise. The image of these governments was determined by their integrity, vision, and responsiveness to the aspirations of the populace. This study was designed to determine the popular image of the imperial governments of Menelik II and Haile Selasse I as reflected in Amharic folk poetry. Without prejudice to some odes which invariably idealise the vision of these monarchs, the politically-inspired Amharic folk poetry is found to be critical of the feudal status quo thus perpetuating its negative images. This underpins the partial unpopularity of Menilik and Haile Selasse. However, these critical gestures would by no means undermine their monumental contributions to the reunification, modernization, and survival of Ethiopia. Thus, the contemporary Amharic folk-poetry is neither iconoclastic nor idealistic but an impassioned allegory of the nation-state.
基金Project supported by the National Natural Science Foundation of China(Nos.61702454 and 61772468)the MOE Project of Humanities and Social Sciences,China(No.17YJC870018)+1 种基金the Fundamental Research Funds for the Provincial Universities of Zhejiang Province,China(No.GB201901006)the Philosophy and Social Science Planning Fund Project of Zhejiang Province,China(No.20NDQN260YB)
文摘Classifying single-trial electroencephalogram(EEG)based motor imagery(MI)tasks is extensively used to control brain-computer interface(BCI)applications,as a communication bridge between humans and computers.However,the low signal-to-noise ratio and individual differences of EEG can affect the classification results negatively.In this paper,we propose an improved common spatial pattern(B-CSP)method to extract features for alleviating these adverse effects.First,for different subjects,the method of Bhattacharyya distance is used to select the optimal frequency band of each electrode including strong event-related desynchronization(ERD)and event-related synchronization(ERS)patterns;then the signals of the optimal frequency band are decomposed into spatial patterns,and the features that can describe the maximum differences of two classes of MI are extracted from the EEG data.The proposed method is applied to the public data set and experimental data set to extract features which are input into a back propagation neural network(BPNN)classifier to classify single-trial MI EEG.Another two conventional feature extraction methods,original common spatial pattern(CSP)and autoregressive(AR),are used for comparison.An improved classification performance for both data sets(public data set:91.25%±1.77%for left hand vs.foot and84.50%±5.42%for left hand vs.right hand;experimental data set:90.43%±4.26%for left hand vs.foot)verifies the advantages of the B-CSP method over conventional methods.The results demonstrate that our proposed B-CSP method can classify EEG-based MI tasks effectively,and this study provides practical and theoretical approaches to BCI applications.
