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Įvairūs grafo srautų minimizavimo arba maksimizavimo uždaviniai yra taikomi modeliuoti procesams logistikoje, kompiuteriniuose tinkluose, akcijų biržose, automobilių eisme ir t.t. Tokio uždavinio sprendimas esant dideliems grafams yra labai sudėtingas, todėl modelyje būna mažai kintančių parametrų arba modeliuojama tik dalis proceso. Tokio uždavinio pavyzdys (kuris ir bus nagrinėjamas) yra eismo modeliavimas keliuose. Kiekvienas vairuotojas bando pasiekti savo tikslą per minimalų galimą tuo metu esančiomis sąlygomis laiką. Tokiu būdu yra užimama „geriausia vieta“ kelyje, o kitiems vairuotojams užimtas kelias gali tapti neberacionalus ir bus pasirenkamas alternatyvus. Šioje vietoje atsispindi esminė tokio tipo uždavinio savybė: kiekvienas proceso dalyvis siekia maksimalios naudos sau, tokiu būdu tą naudą atimdamas iš kitų dalyvių. Šiu atveju „nauda“ yra vieta eisme. Darbe yra aprašytas eismo imitavimo sistemos modelis ir realizuotas tokia architektūra, kuri tinkama lygiagretiems skaičiavimams. Pateikta statistiniai gauto modelio analizavimo pavyzdžiai. Taip pat pasiūlyti keli algoritmai specifiniams uždaviniams spręsti, kaip dalinis modelio perskaičiavimas. / In this work we will try to apply various path search algorithm optimizations for solving traffic simulation problem. These optimizations are made on the basis of processes and patterns specific to car traffic. Other areas like logistics, money traffic and stocks should have their own specific optimizations. Primary selection criteria will be calculation time. Errors are also introduced by these optimizations, but benefits of solving more complex problems in much shorter time will outweigh those errors. Most of described algorithms are just modifications of traditional Dijkstra's algorithm. This allows to show step by step every optimization introduced, which we can split into 3 categories: Algorithms for finding shortest path in untouched graph, Algorithms for finding shorted path which need modified graph, Algorithms specific for traffic simulation. Algorithms up to graph transformations have been analyzed in previous works. These optimizations proved to be very perspective in point-to-point path search. Thou applying them to traffic modeling and introducing modeling specific optimizations is a relatively new research area. Also an algorithm imitating traffic laws has to be implemented. One of suggested optimizations could be called “fast partial recalculation”. This would allow a faster recalculation of main path loads. Assuming that traffic is the same and graph is slightly modified. A modified idea could be adapted for a recalculation with modified traffic loads. Vastly... [to full text]

In this paper we propose an unsupervised voting-merging scheme that is capable of clustering data sets, and also of finding the number of clusters existing in them. The voting part of the algorithm allows us to combine several runs of clustering algorithms resulting in a common partition. This helps us to overcome instabilities of the clustering algorithms and to improve the ability to find structures in a data set. Moreover, we develop a strategy to understand, analyze and interpret these results. In the second part of the scheme, a merging procedure starts on the clusters resulting by voting, in order to find the number of clusters in the data set. / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

In this paper we introduce a mixed approach for the semi-supervised data problem. Our approach consists of an ensemble unsupervised learning part where the labeled and unlabeled points are segmented into clusters. Continuing, we take advantage of the a priori information of the labeled points to assign classes to clusters and proceed to predicting with the ensemble method new incoming ones. Thus, we can finally conclude classifying new data points according to the segmentation of the whole set and the association of its clusters to the classes. / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Seminario para optar al Título de Ingeniero Comercial Mención Economía / En la actualidad coexisten distintas definiciones de cluster, las cuales entregan visiones alternativas de cómo abordar el análisis y desarrollo de clusters. Para estas definiciones, distintas teorías explican su surgimiento, pero todas entregan una base común en cuanto a que el mayor determinante de las ventajas generadas por clusters proviene de las relaciones que existan entre los agentes, ya sea una relación dada solo por la ubicación dentro de una zona geográfica, o una relación forjada a través de la interacción repetitiva y una toma de decisiones en conjunto. Los beneficios que se obtienen de una relación industrial tipo cluster provienen de 3 grandes fuentes: Aumentos en productividad, mejoras en su capacidad de innovar y atracción de nuevas empresas al sistema.

La recherche de nouveaux métabolites d'intérêt médical est toujours d'actualité, surtout si l'on considère que d'anciennes, mais aussi des nouvelles infections bactériennes ou virales apparaissent régulièrement. Les actinomycètes, et plus particulièrement les Streptomyces, sont les principaux producteurs de molécules anti-microbiennes. En effet, ils produisent presque 60-70% des produits naturels d'origine microbienne. La plupart de ces métabolites appartient à la classe des polycétides, qui sont synthétisés par des complexes multienzymatiques, les polycétide-synthétases (PKS). Les PKS utilisent des acides gras simples pour assembler des structures polycétidiques très diversifiées. Une approche très prometteuse pour identifier des nouvelles voies de biosynthèse de métabolites secondaires est basée sur une approche génomique ou « genome mining ». Le séquençage du chromosome linéaire de Streptomyces ambofaciens ATCC23877 a, entre autre, révélé sur le bras chromosomique droit, un cluster cryptique de gènes de PKS de type I de grande taille. Ce cluster contient 25 gènes, dont 9 gènes de biosynthèse, pour un total de 25 modules, tous fonctionnels. Les analyses in silico des gènes de PKS ont permis de prédire que le cluster serait responsable de la synthèse d'une molécule appartenant à la famille des macrolides. Dans des conditions standard de laboratoire, le cluster était silencieux. Afin d'activer l'expression du cluster, un gène de régulation, samR0484, présent dans le cluster et codant un régulateur de la famille LAL (Large ATP binding protein of the LuxR family), a été surexprimé dans la souche sauvage. Les analyses transcriptionelles ont montré que cela se traduisait par l'induction de l'expression des gènes de biosynthèse. Par conséquence, une stratégie de « comparative metabolic profiling » a été menée entre la souche sauvage et la souche mutante afin d'identifier le nouveau métabolite. Quatre formes différentes d'un macrolide avec un cycle lactonique de 50 carbones, ont été isolées et caractérisées. Ces composants, nommés sambomycine A, B, C et D, ont montré une activité antibactérienne et une activité antiproliférative intéressante. La détermination de la structure de la sambomycine a révélé des caractéristiques uniques et intéressantes, concernant la réaction de cyclisation et la synthèse d'un précurseur atypique. Ces mécanismes de biosynthèse ont fait l'objet d'une étude plus approfondie. Nous nous sommes également intéressés à la régulation de ce cluster. Le régulateur LAL agit comme un activateur transcriptionnel essentiel. Des analyses préliminaires indiquent que ce régulateur se fixe aux régions promotrices de certains gènes, notamment celles des gènes de biosynthèse ainsi que celles d'autres gènes de post-modification, activant ainsi leur transcription. / The constant and urgent need of novel bioactive compounds is the result of the emergence in the last decades of new and old infectious diseases, a sore for humankind. Actinomycetes and especially the genus Streptomyces are the principal producers of microbial drugs producing nearly 60-70% of the natural products. The majority of secondary metabolites belong to the class of polyketides that are synthesised by multienzymatic complexes named polyketides synthases (PKS). PKSs condensate simple small carboxylic acids to generate a wide range of complex polyketide structures. In the search for new drugs, the genome mining approach proved to be a powerful tool in the identification of cryptic secondary metabolite pathways. The sequencing and the analysis of Streptomyces ambofaciens ATCC23877 genome has revealed a large type I PKS cluster, on the right arm of the chromosome. The cluster contains 9 PKS, composed of 25 functional modules. In silico analysis of the PKS genes and of the tailoring genes enabled to predict the structure of the expected metabolite, a macrolide. In the laboratory standard conditions, the cluster showed to be silent. Therefore, to promote the expression of the cluster, the regulatory gene samR0484, encoding a LAL regulator (Large ATP binding protein of the LuxR family) was overexpressed in the wt strain. Transcriptional analyses showed that the PKS genes were expressed. Subsequently, by comparative metabolic profiling between the mutant strain and the wt, we were able to detect the novel metabolite produced by S. ambofaciens. Structural elucidation revealed four form of a 50-membered macrolide, named sambomycin. The compounds endow antibacterial and antitumoral activities. The structure unveiled unique and interesting characteristics of sambomycin, i.e. the cyclization reaction and the presence of an atypical extender unit. The mechanisms of biosynthesis have been analysed more in details in this work. We also investigated in the regulation of the cluster. The LAL regulator was shown to be an essential transcriptional activator, binding to the promoter regions of the PKS genes and probably to other genes in the cluster.