43 research outputs found
DĂ©veloppement dâune solution dâinformatique dĂ©cisionnelle au sein de GuĂ©rin et Guinnard Ă©lectricitĂ© SA
Ce travail a pour mission la crĂ©ation dâune solution dâinformatique dĂ©cisionnelle au sein de GuĂ©rin et Guinnard Ă©lectricitĂ© SA. Comme dĂ©crit dans le mandat du travail de Bachelor, ce projet est constituĂ© de plusieurs objectifs. Le principal est celui de dĂ©livrer une application Ă lâentreprise, utile Ă la prise de dĂ©cisions. Les objectifs accessoires sont lâĂ©tablissement dâun Ă©tat des lieux du matĂ©riel informatique et du systĂšme dâinformation, une analyse des besoins selon les informations dont lâentreprise dispose ou peut disposer et lâĂ©laboration dâune solution pour la crĂ©ation dâune application. (Pot, Mandat du travail de Bachelor, 2013) La mĂ©thodologie consiste, dans un premier temps, Ă Ă©tablir Ă un Ă©tat des lieux du systĂšme dâinformations. Avec les informations disponibles, une solution est conçue en collaboration avec les exigences de lâentreprise. La derniĂšre Ă©tape consiste Ă la crĂ©ation de lâapplication et Ă son instauration dans lâentreprise. Le rĂ©sultat Ă©tant en accord avec les objectifs ci-dessus, de nombreux constats ont Ă©tĂ© observĂ©s quant Ă la gestion de lâinformation au sein de lâentreprise, ce qui permet lâĂ©laboration de recommandations quant Ă lâimportance de la saisie, la crĂ©ation dâinformations supplĂ©mentaires et pertinentes. Ce travail permet Ă©galement Ă lâentreprise dâavoir une importante prise de conscience et une remise en question face Ă son systĂšme dâinformation
Covariance and Correlation Kernels on a Graph in the Generalized Bag-of-Paths Formalism
This work derives closed-form expressions computing the expectation of
co-presence and of number of co-occurrences of nodes on paths sampled from a
network according to general path weights (a bag of paths). The underlying idea
is that two nodes are considered as similar when they often appear together on
(preferably short) paths of the network. The different expressions are obtained
for both regular and hitting paths and serve as a basis for computing new
covariance and correlation measures between nodes, which are valid positive
semi-definite kernels on a graph. Experiments on semi-supervised classification
problems show that the introduced similarity measures provide competitive
results compared to other state-of-the-art distance and similarity measures
between nodes
Estimation of flow trajectories in a multi-lines transportation network
Characterizing a public transportation network, such as an urban network with multiple lines, requires the originâdestination trip counts during a given period. Yet, if automatic counting makes the embarkment (boarding) and disembarkment (alighting) counts in vehicles known, it often happens that pedestrian transfers between lines are harder to track, and require costly and invasive devices (e.g., facial recognition system) to be estimated. In this contribution, we propose a method, based on maximum entropy and involving an iterative fitting procedure, which estimates the passenger flow between origins and destinations solely based on embarkment and disembarkment counts. Moreover, this method is flexible enough to provide an adaptable framework in case additional data is known, such as attraction poles between certain nodes in the network, or percentages of transferring passengers between some lines. This method is tested on toy examples, as well as with the data of the public transportation network of the city of Lausanne provided by its Transportation Agency (tl), and gives arguably convincing estimations of the transportation flow
Randomized Optimal Transport on a Graph: framework and new distance measures
The recently developed bag-of-paths (BoP) framework consists in setting a
Gibbs-Boltzmann distribution on all feasible paths of a graph. This probability
distribution favors short paths over long ones, with a free parameter (the
temperature ) controlling the entropic level of the distribution. This
formalism enables the computation of new distances or dissimilarities,
interpolating between the shortest-path and the resistance distance, which have
been shown to perform well in clustering and classification tasks. In this
work, the bag-of-paths formalism is extended by adding two independent equality
constraints fixing starting and ending nodes distributions of paths (margins).
When the temperature is low, this formalism is shown to be equivalent to a
relaxation of the optimal transport problem on a network where paths carry a
flow between two discrete distributions on nodes. The randomization is achieved
by considering free energy minimization instead of traditional cost
minimization. Algorithms computing the optimal free energy solution are
developed for two types of paths: hitting (or absorbing) paths and non-hitting,
regular, paths, and require the inversion of an matrix with
being the number of nodes. Interestingly, for regular paths on an undirected
graph, the resulting optimal policy interpolates between the deterministic
optimal transport policy () and the solution to the
corresponding electrical circuit (). Two distance
measures between nodes and a dissimilarity between groups of nodes, both
integrating weights on nodes, are derived from this framework.Comment: Preprint paper to appear in Network Science journal, Cambridge
University Pres
Sparse Randomized Shortest Paths Routing with Tsallis Divergence Regularization
This work elaborates on the important problem of (1) designing optimal
randomized routing policies for reaching a target node t from a source note s
on a weighted directed graph G and (2) defining distance measures between nodes
interpolating between the least cost (based on optimal movements) and the
commute-cost (based on a random walk on G), depending on a temperature
parameter T. To this end, the randomized shortest path formalism (RSP,
[2,99,124]) is rephrased in terms of Tsallis divergence regularization, instead
of Kullback-Leibler divergence. The main consequence of this change is that the
resulting routing policy (local transition probabilities) becomes sparser when
T decreases, therefore inducing a sparse random walk on G converging to the
least-cost directed acyclic graph when T tends to 0. Experimental comparisons
on node clustering and semi-supervised classification tasks show that the
derived dissimilarity measures based on expected routing costs provide
state-of-the-art results. The sparse RSP is therefore a promising model of
movements on a graph, balancing sparse exploitation and exploration in an
optimal way
Randomized Shortest Paths with Net Flows and Capacity Constraints
This work extends the randomized shortest paths (RSP) model by investigating
the net flow RSP and adding capacity constraints on edge flows. The standard
RSP is a model of movement, or spread, through a network interpolating between
a random-walk and a shortest-path behavior [30, 42, 49]. The framework assumes
a unit flow injected into a source node and collected from a target node with
flows minimizing the expected transportation cost, together with a relative
entropy regularization term. In this context, the present work first develops
the net flow RSP model considering that edge flows in opposite directions
neutralize each other (as in electric networks), and proposes an algorithm for
computing the expected routing costs between all pairs of nodes. This quantity
is called the net flow RSP dissimilarity measure between nodes. Experimental
comparisons on node clustering tasks indicate that the net flow RSP
dissimilarity is competitive with other state-of-the-art dissimilarities. In
the second part of the paper, it is shown how to introduce capacity constraints
on edge flows, and a procedure is developed to solve this constrained problem
by exploiting Lagrangian duality. These two extensions should improve
significantly the scope of applications of the RSP framework
The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases
The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article