858 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Generalized logarithmic sheaf on smooth projective surfaces
We define the notion of generalized logarithmic sheaves on a smooth
projective surface, associated to a pair consisting of a reduced curve and some
fixed points on it. We then set up the study of the Torelli property in this
setting, focusing mostly in the case of the blow-up of the projective plane on
a reduced set of points and, in particular, in the case of the cubic surface.
We also study the stability property of generalized logarithmic sheaves as well
as carrying out the description of their moduli spaces.Comment: 39 pages. To appear in International Mathematics Research Notices.
Comments are welcom
"Le present est plein de l’avenir, et chargé du passé" : Vorträge des XI. Internationalen Leibniz-Kongresses, 31. Juli – 4. August 2023, Leibniz Universität Hannover, Deutschland. Band 3
[No abstract available]Deutschen Forschungsgemeinschaft (DFG)/Projektnr. 517991912VGH VersicherungNiedersächsisches Ministerium für Wissenschaft und Kultur (MWK
Are the Collatz and abc conjectures related?
The Collatz and conjectures, both well known and thoroughly studied,
appear to be largely unrelated at first sight. We show that assuming the
conjecture true is helpful to improve the lower bound of integers initiating a
particular type of Collatz sequences, namely finite sequences of a given length
where all terms but one are odd with the usual ``shortcut'' form. To obtain
sharper bounds in this context, we are led to consider a small subset of the
-hits. Then, it turns out that Collatz iterations as well as Wieferich
primes may be used to find large triples in this subset
Decisions, decisions, decisions: the development and plasticity of reinforcement learning, social and temporal decision making in children
Human decision-making is the flexible way people respond to their environment, take actions, and plan toward long-term goals. It is commonly thought that humans rely on distinct decision-making systems, which are either more habitual and reflexive or deliberate and calculated. How we make decisions can provide insight into our social functioning, mental health and underlying psychopathology, and ability to consider the consequences of our actions. Notably, the ability to make appropriate, habitual or deliberate decisions depending on the context, here referred to as metacontrol, remains underexplored in developmental samples. This thesis aims to investigate the development of different decision-making mechanisms in middle childhood (ages 5-13) and to illuminate the potential neurocognitive mechanisms underlying value-based decision-making. Using a novel sequential decision-making task, the first experimental chapter presents robust markers of model-based decision-making in childhood (N = 85), which reflects the ability to plan through a sequential task structure, contrary to previous developmental studies. Using the same paradigm, in a new sample via both behavioral (N = 69) and MRI-based measures (N = 44), the second experimental chapter explores the neurocognitive mechanisms that may underlie model-based decision-making and its metacontrol in childhood and links individual differences in inhibition and cortical thickness to metacontrol. The third experimental chapter explores the potential plasticity of social and intertemporal decision-making in a longitudinal executive function training paradigm (N = 205) and initial relationships with executive functions. Finally, I critically discuss the results presented in this thesis and their implications and outline directions for future research in the neurocognitive underpinnings of decision-making during development
Branching points in the planar Gilbert--Steiner problem have degree 3
Gilbert--Steiner problem is a generalization of the Steiner tree problem on a
specific optimal mass transportation.
We show that every branching point in a solution of the planar
Gilbert--Steiner problem has degree 3
Obtención del mínimo árbol expandido en el problema de Steiner Euclídeo
Se analizará el problema de Steiner Euclídeo con el objetivo de buscar el
mínimo árbol expandido que conecte un conjunto finito de puntos del plano
euclídeo. Se representarán gráficamente los árboles de Steiner en el contexto
de grafos no dirigidos y con pesos ponderados en sus aristas.
Se estudiará la modelización del problema de Steiner como un diseño de redes
con costes fijos y, para ejemplificar la resolución manual del problema de
Steiner, se expondrán algunos ejemplos relativamente sencillos para su
implementación con intención de poder aplicarse en problemas de mayor
complejidad que requieran cierta dificultad y rapidez computacional.
Se comentará también la versión con distancias rectilíneas donde las
conexiones estarán restringidas, sólo podrán ser horizontales o verticales.The Euclidean Steiner problem will be analyzed in order to find the minimum
expanded tree that connects a finite set of points in the Euclidean plane. Steiner
trees will be represented graphically in the context of undirected graphs and
with weighted weights on their edges.
The modeling of the Steiner problem will be studied as a design of networks
with fixed costs and, to exemplify the manual resolution of the Steiner problem,
some relatively simple examples will be presented for its implementation with
the intention of being able to apply it to more complex problems that require
some difficulty. and computational speed.
The version with rectilinear distances will also be commented where the
connections will be restricted, they can only be horizontal or vertical.Departamento de Estadística e Investigación OperativaGrado en Ingeniería en Organización Industria
Planejamento de caminhos 3D em ambiente estático
Orientador: André Luiz Pires GuedesTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa : Curitiba, 03/05/2023Inclui referênciasÁrea de concentração: Ciência da ComputaçãoResumo: O Planejamento de caminhos no R3 é um problema computacional que tem despertado o interesse dos pesquisadores por sua vasta aplicabilidade em otimização. Dados um ambiente 3D com obstáculos, um ponto origem e um ponto destino, a resposta esperada é se existe algum caminho, livre de obstáculos, entre origem e destino e havendo, qual dos caminhos minimiza custo. Este problema pertence à classe de complexidade computacional NP-Difícil. A presente pesquisa se propõe a estudar este problema e propor técnicas que permitam obter o caminho mínimo em tempo computacional razoável. A pesquisa consiste em elaborar algoritmos, propor otimizações, analisar seus desempenhos e qualidade dos seus resultados na intenção de, pelo menos, se aproximar do ótimo em tempo polinomial. Apesar de se vislumbrar inúmeras aplicações práticas, a pesquisa se atém apenas a propor variações do algoritmo planejador que recebe dados do ambiente e retorna um caminho a ser seguido, ignorando como os dados de entrada foram obtidos e como os dados de saída se converterão em ações posteriormente. Este trabalho propõe com otimizações simples que em teoria reduzem drasticamente o custo computacional para este problema no caso geral.Abstract: Path planning inR3 is a computational problem that has aroused the interest of researchers due to its wide applicability in optimization. Given a 3D environment with obstacles, a source point and a target point, the expected answer is whether there is a path, free of obstacles, between source and target and if so, which path minimizes cost. This problem belongs to the NP-Hard computational complexity class. This research proposes to study this problem and propose techniques that allow obtaining the shortest path in reasonable computational time. The research consists of developing algorithms, proposing optimizations, analyzing their performance and the quality of their results with the intention of at least approaching the optimum in polynomial time. Despite envisioning numerous practical applications, the research just sticks to proposing variations of the planner algorithm that receives data from the environment and returns a path to be followed, ignoring how the input data were obtained and how the output data will be converted into actions posteriorly. This work proposes simple optimizations that in theory drastically reduce the computational cost for this problem in the general case
2010 GREAT Day Program
SUNY Geneseo’s Fourth Annual GREAT Day.
This file has a supplement of three additional pages, linked in this record.https://knightscholar.geneseo.edu/program-2007/1004/thumbnail.jp
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