Universalization or localization? Issues of knowledge legitimation in comaprative education

The endeavor to unite the universal and the accidental in both, the physical and the social world into one theoretical framework – the idea of such a unity can be found already in the Chinese concept of Tao – dates back in the modern culture to the Enlightenment. Such a unified knowledge came to be understood as a potential tool of forecasting and controlling societal progress. All through the positivistic 19th century, comparativists followed Marc-Antoine Jullien de Paris, who thought educational comparison should become an exact science whose outcomes could be used anywhere and transplanted to any place. It was Michael Sadler who as the first comparative educationalist strictly refused the idea of cultural and institutional borrowing. Under his influence comparative education focused on the variations unique to the single countries and to the factors underlying these variations. Even the later emerging functionalist method remained in the tradition of a „one-dimensional logic“, which, as Marcuse alleged, was inseparably connected with the rationale of domination of nature and society. It is only the postmodern sight, which – without giving up the humanistic ideas of modernity which originated in Western modernization – opens possibilities to enter a cross cultural dialogue and to accept multiple theoretical realities. (DIPF/Orig.)Der Beitrag bietet einen breiten Überblick über grundlegende Tendenzen in der historischen Entwicklung von Vergleichender Erziehungswissenschaft. Dabei unterliegt der Darstellung implizit und explizit durchgängig das Bewußtsein, daß vergleichende Wissenschaft im weitesten Sinne weder ein Monopol der jüngsten Epoche noch etwa eines einzigen Kulturraums darstellt. Mit seiner analytischen, aber auch normativen Interpretation von gegenwärtigen Tendenzen postmodernen Denkens sieht er die Möglichkeit eines transkulturellen Dialogs über die Weiterentwicklung und Erweiterung der etablierten (westlichen) Vergleichenden (Erziehungs-)Wissenschaft. (DIPF/Orig.

Perspectives From Different Levels Of Management Teams On Business And Information Systems Strategies Alignment – A Case Of Alpha Networks Inc.

When formulating their business strategies, companies are influenced by both the internal and external environments. Strategic alignment has been studied extensively for more that two decades, most research has focused are on the strategic alignment between business strategy and information systems [9][21][24]. Few works have studied the relationship between business strategies and IS alignment from the perspective of different levels of management. This study uses questionnaires and interviews to analyze the perspectives of thirty-three managers from different departments. The findings show that the higher an executive’s level, the greater the alignment perceived between the company’s businesses and IS strategies

A Qualitative Research on Marketing and Sales in the Artificial Intelligence Age

The age of artificial intelligence is here! Artificial Intelligence, robotics, machine learning, and automation are impacting the field of marketing and sales in an unprecedented way. In this study, the qualitative research methodology will be used to better understand the revolution and evolution of marketing and sales field in the AI age. Multiple case studies will be performed in various marketing and sales units in different organizations. This research is of value to both academics and practitioners as it aims to provide a detailed analysis and documentation of the changes in marketing and sales functionalities and job markets as AI technology advances

EFFICIENT APPROXIMATION FOR LARGE-SCALE KERNEL CLUSTERING ANALYSIS

Kernel k-means is useful for performing clustering on nonlinearly separable data. The kernel k-means is hard to scale to large data due to the quadratic complexity. In this paper, we propose an approach which utilizes the low-dimensional feature approximation of the Gaussian kernel function to capitalize a fast linear k-means solver to perform the nonlinear kernel k-means. This approach takes advantage of the efficiency of the linear solver and the nonlinear partitioning ability of the kernel clustering. The experimental results show that the proposed approach is much more efficient than a normal kernel k- means solver and achieves similar clustering performance

Liquid-gas Phase Transition in Strange Hadronic Matter with Weak Y-Y Interaction

The liquid-gas phase transition in strange hadronic matter is reexamined by using the new parameters about the $\Lambda - \Lambda$ interaction deduced from recent observation of $^{6}_{\Lambda\Lambda}He$ double hypernucleus. The extended Furnstahl-Serot-Tang model with nucleons and hyperons is utilized. The binodal surface, the limit pressure, the entropy, the specific heat capacity and the Caloric curves are addressed. We find that the liquid-gas phase transition can occur more easily in strange hadronic matter with weak Y-Y interaction than that of the strong Y-Y interaction.Comment: 10 pages, 7 figure

Filter Bank Common Spatial Pattern Algorithm on BCI Competition IV Datasets 2a and 2b

The Common Spatial Pattern (CSP) algorithm is an effective and popular method for classifying 2-class motor imagery electroencephalogram (EEG) data, but its effectiveness depends on the subject-specific frequency band. This paper presents the Filter Bank Common Spatial Pattern (FBCSP) algorithm to optimize the subject-specific frequency band for CSP on Datasets 2a and 2b of the Brain-Computer Interface (BCI) Competition IV. Dataset 2a comprised 4 classes of 22 channels EEG data from 9 subjects, and Dataset 2b comprised 2 classes of 3 bipolar channels EEG data from 9 subjects. Multi-class extensions to FBCSP are also presented to handle the 4-class EEG data in Dataset 2a, namely, Divide-and-Conquer (DC), Pair-Wise (PW), and One-Versus-Rest (OVR) approaches. Two feature selection algorithms are also presented to select discriminative CSP features on Dataset 2b, namely, the Mutual Information-based Best Individual Feature (MIBIF) algorithm, and the Mutual Information-based Rough Set Reduction (MIRSR) algorithm. The single-trial classification accuracies were presented using 10 × 10-fold cross-validations on the training data and session-to-session transfer on the evaluation data from both datasets. Disclosure of the test data labels after the BCI Competition IV showed that the FBCSP algorithm performed relatively the best among the other submitted algorithms and yielded a mean kappa value of 0.569 and 0.600 across all subjects in Datasets 2a and 2b respectively