Computational Science and Techniques

This paper presents the protons and neutrons distributions in atomic nucleus shells calculation algorithm which may be used for ab initio no-core nuclear shell model computations. The problem of enumeration of many-particle states is formulated on energetic basis instead of application of the traditional scheme for states classification. The algorithm provides calculations of protons and neutrons occupation restrictions for nuclear shells for an arbitrary number of oscillator quanta. The reported results show that the presented algorithm significantly outperforms the traditional approach and may fit the needs of state-of-the-art no-core shell model calculations of atomic nuclei.

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.

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.

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).