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Moving Forces
(2017)
Throughout a large part of the twentieth century, the body was interpreted as a field of signs, the meaning of which pointed to an unconscious dimension. At the height of the popularity of structuralism, Jacques Lacan deemed the unconscious to be “structured like a language.” Starting in the early 1990s, however, a deep shift occurred in the way the body was interpreted. A new movement cast tremendous doubt on the hegemony of language and instead advocated a performative, pictorial, and affective approach — the so-called material turn — which encompassed all of these. In the words of Karen Barad, this turn inquired as to why meaning, history, and truth are assigned to language only, whereas the movements of materiality are given less prominence: “How did language come to be more trustworthy than matter? Why are language and culture granted their own agency and historicity while matter is figured as passive and immutable?” With this shift toward the material, bodies began to be seen in a different light and their materiality understood as something that follows its own laws and movements, which cannot be understood exclusively in terms of social-cultural codes. Instead, these laws and movements call into question the very dichotomies of nature/culture and body/spirit.
Selection of initial points, the number of clusters and finding proper clusters centers are still the main challenge in clustering processes. In this paper, we suggest genetic algorithm based method which searches several solution spaces simultaneously. The solution spaces are population groups consisting of elements with similar structure. Elements in a group have the same size, while elements in different groups are of different sizes. The proposed algorithm processes the population in groups of chromosomes with one gene, two genes to k genes. These genes hold corresponding information about the cluster centers. In the proposed method, the crossover and mutation operators can accept parents with different sizes; this can lead to versatility in population and information transfer among sub-populations. We implemented the proposed method and evaluated its performance against some random datasets and the Ruspini dataset as well. The experimental results show that the proposed method could effectively determine the appropriate number of clusters and recognize their centers. Overall this research implies that using heterogeneous population in the genetic algorithm can lead to better results.
The German Enlightenment
(2017)
The term Enlightenment (or Aufklärung) remains heavily contested. Even when historians delimit the remit of the concept, assigning it to a particular historical period rather than to an intellectual or moral programme, the public resonance of the Enlightenment remains high and problematic—especially when equated in an essentialist manner with modernity or some core values of ‘the West’. This Forum has been convened to discuss recent research on the Enlightenment in Germany, different views of the term and its ideological use in public discourse outside academia (and sometimes within it).