Inspired by human learning mechanisms, a novel meta-heuristic algorithm named human learning optimization (HLO) is presented in this paper in which the individual learning operator, social learning operator, random exploration learning operator and re-learning operator are developed to generate new solutions and search for the optima by mimicking the human learning process. Then HLO is applied to solve the well-known 5.100 and 10.100 multi-dimensional knapsack problems from the OR-library and the performance of HLO is compared with that of other meta-heuristics collected from the recent literature. The experimental results show that the presented HLO achieves the best performance in comparison with other meta-heuristics, which demonstrates that HLO is a promising optimization tool.
The article discusses the overall interpretation of the War of 1812 and the heroization and deheroization of its key figures. Changing political circumstances, including the Tsars' orders concerning the representation of the Russian Empire's past and nationbuilding projects propagated by Russian elites constituted key variables. Between 1812 and 1914, preachers, artists, journalists, rulers, military officers, authors of memoirs, civil and military historians, writers and journalists participated in a dispute over the 'heroes' and 'villains' of the 1812 war. The present study draws on sources from the 19th and early 20th century such as the history of Aleksandr Michailovskii Danilevskii, the memoirs of Aleksei Er-molov, Nadezhda Durova and Denis Davydov, lyrics by Vasilii Zhukovskii, and Lev Tolstoi's novel War and Peace. It compares and contrasts these author's statements and ideas with the visual, poetic, journalistic and commemorative imagery of their time. Such an approach helps explain how heroic characters were designed and demonstrates the ambivalence of their positions: the frequently cyclical dynamic of appearance and disappearance from mainstream narratives of Russian history. This approach also allows for the attribution of individual narratives to specific discursive genres. Genetic source criticism was applied when analyzing War and Peace. Tolstoi's drafts and notes are examined to reveal the ways in which his concept of the novel changed over time, including gradual revisions in the shaping of characters and the use of the memories of war veterans to create a grand narrative. All this allows for an identification of the techniques Tolstoi applied when working with historical evidence, his recoding of the cultural and psychological profiles of certain characters, his retouching of contradictory elements, and his omission of a vast number of facts. The authors conclude that the heroization techniques applied in these narratives strongly depended upon the philosophy of history of their time. Thus, in the 1820-30's the trend towards romanticizing and nationalizing the Russian past manifested itself in a desacralization of Emperor Alexander I and a substitution of the idea of a "people's war" for that of a "holy war". By contrast, Lev Tolstoi's national project meant that the writer depersonalized war and heroized the Russian family and the Russian people. Later on, this discourse was reinforced through the sociologization of the writing of history, which meant that historians presented the war of 1812 as a clash of abstract interests, processes, and groups, to which the names of heroes served as accessories. © Franz Steiner Verlag GmbH, Stuttgart/Germany.
We review and explain an infinite-dimensional counterpart of the Hurwitz theory realization (Alexeevski and Natanzon, Math. Russ. Izv. 72:3-24, 2008) of algebraic open-closed-string model à la Moore and Lazaroiu, where the closed and open sectors are represented by conjugation classes of permutations and the pairs of permutations, i.e. by the algebra of Young diagrams and bipartite graphs, respectively. An intriguing feature of this Hurwitz string model is the coexistence of two different multiplications, reflecting the deep interrelation between the theory of symmetric and linear groups, S∞ and GL(∞).
Гибрид двух новых методов, спектральной кластеризации и метод таксономии - применяется для анализа научно-исследовательской деятельности кафедры. Приведенн пример, иллюстрирующий этот метод, который применяется для решения реальных задач.
Трансформация исследований и разработок в России.
Large deviation rates are obtained for suspension flows over symbolic dynamical systems with a countable alphabet. The method is that of the first author and follows that of Young. A corollary of the main results is a large deviation bound for the Teichm¨uller flow on the moduli space of abelian differentials, which extends earlier work of J. Athreya.