Klaipėdos universitetas

Selected find spots along the Swedish coast of the Baltic Sea are presented, in order to illustrate different ways in which hunter-gatherer societies related to the coast during the Mesolithic. Transformations of the landscape were mainly due to isostatic and eustatic changes. In the northern part, the land rose, forming new coasts and archipelagos at a speed that was noticeable even within one generation. Similar rapid changes occurred in the southern area, but in the opposite direction, with large areas of coast being submerged. Both physical and mental reactions to this are explored.

The article deals with the main range of problems of Grensk culture in the Final Palaeolithic and Mesolithic in the Upper Dnieper region. At present, the understanding of the ways and mechanisms of the formation and the time of habitation of members of this ancient culture are rather debatable. Interpretations of the sources have resulted in two completely different research approaches in terms of methodology, bringing together supporters of the indigenous (U. Budzko, V. Kapytsin, A. Kalechyts, G. Sinitsyna, etc) or migration (L. Zaliznyak, U. Ksiandzou, A. Sorokin, etc) ways of the emergence and the development of Grensk culture. It is impossible to understand the essence of the ‘Grensk question’ without considering the nature of its origin, the problem looked at in this article.

The process of the recolonisation of northern Europe after deglaciation is related to groups of hunter-gatherer societies called

In this paper, we are analyzing the results of native Lithuanian speaker recognition and identification using long short-term memory deep neural network. We look at recognition accuracy and identify further potential improvements. Dataset used for training and speaker recognition consists of over 370 unique speakers, who provide their voice utterances in Lithuanian language. In this paper we present results that are derived from part of this dataset.

Population initialization is one of the important tasks in evolutionary and genetic algorithms (GAs). It can affect considerably the speed of convergence and the quality of the obtained results. In this paper, some heuristic strategies (procedures) for construction of the initial populations in genetic algorithms are investigated. The purpose is to try to see how the different population initialization strategies (procedures) can influence the quality of the final solutions of GAs. Several simple procedures were algorithmically implemented and tested on one of the hard combinatorial optimization problems, the quadratic assignment problem (QAP). The results of the computational experiments demonstrate the usefulness of the proposed strategies. In addition, these strategies are of quite general character and may be easily transferred to other population-based metaheuristics (like particle swarm or bee colony optimization methods).

Occurrence of the agent paradigm and its further applications have stimulated the emergence of new concepts and methodologies in computer science. Today terms like multi-agent system, agent-oriented methodology, and agent-oriented programming (AOP) are widely used. The aim of this paper is to clarify the validity of usage of the terms AOP and AOP language. This is disclosed in two phases of an analysis process. Determining to which concepts, terms like agent, programming, object-oriented analysis and design, object-oriented programming, and agent-oriented analysis and design correspond is accomplished in the first phase. Analysis of several known agent system engineering methodologies in terms of key concepts used, final resulting artifacts, and their relationship with known programming paradigms and modern tools for agent system development is performed in the second phase. The research shows that in the final phase of agent system design and in the coding stage, the main artifact is an object, defined according to the rules of the object-oriented paradigm. Hence, we conclude that the computing society still does not have AOP owing to the lack of an AOP language. Thus, the term AOP is very often incorrectly assigned to agent system development frameworks that in all cases, transform agents into objects.

Šiame darbe sudarytas rekurentinis paslėptųjų Markovo modelių parametrų vertinimo algoritmas. Paslėptieji Markovo modeliai modeliuojami Gauso skirstiniu, kurio parametrai pasiskirstę pagal daugiamatį normalųjį dėsnį su nežinomais vidurkių vektoriumi ir kovariacijų matrica. Nežinomų parametrų įverčiai gaunami didžiausio tikėtinumo metodu. Rekurentinis algoritmas sudarytas remiantis didžiausio tikėtinumo metodu išvestomis formulėmis ir klasikiniu EM algoritmu. Kadangi rekurentinio algoritmo vykdymo laikas yra proporcingas apdorojamų stebėjimų skaičiui, tai jis gali būti naudojamas modelio parametrų vertinimui realiu laiku. Realizuoto rekurentinio EM algoritmo savybės buvo ištirtos kompiuteriniu eksperimentu klasterizuojant duomenis. Jis taip pat gali būti taikomas duomenų klasifikavimo ir atpažinimo realiu laiku uždaviniams spręsti.