@conference {251, title = {S3LF: a Socio-Technical System for Self-Determinant Governance in Collaborative Organizations}, booktitle = {23RD INTERNATIONAL PUBLIC MANAGEMENT NETWORK (IPMN) CONFERENCE}, year = {2019}, abstract = {

This work presents S3LF, a socio-technical system in the form of a mobile application for
facilitating a ​ digital self-determinant governance experience in collaborative organizations. It
consists of a technologically mediated adaptation of the decision making framework Sociocracy 3.0
a.k.a S3, turning it into an asynchronous and remote process with a facilitation mediated through the
user experience (UX) and interaction design. S3LF enables digital and distributed organizations
such as Collaborative Networked Organizations (CNOs) to adopt self-determinant governancemethodologies such as S3, and promises a faster onboarding into self-determinant governance and
higher throughput of self-determinant decision making. Furthermore, we introduce in S3LF a
self-diagnosis module that reports the level of self-determination perceived by each decision maker
of the group for each decision made, over different contextual situations; whose analysis has the
potential to allow organizations to self-correct dominant situations.

}, keywords = {collaborative organizations, consent-based decision making, digital governance, socio-technical system, Sociocracy 3.0}, author = {Ribas, Alexandre and Bromberg, Facundo and Dinamarca, Agustina} } @conference {100, title = {Segmentaci{\'o}n de im{\'a}genes en vi{\~n}edos para la medici{\'o}n aut{\'o}noma de variables vit{\'\i}colas}, booktitle = {XVIII Congreso Argentino de Ciencias de la Computaci{\'o}n}, year = {2012}, isbn = {978-987-1648-34-4}, author = {P{\'e}rez, Diego S and Bromberg, Facundo} } @conference {115, title = {Sistema SCADA para monitoreo y control de una central hidroel{\'e}ctrica}, booktitle = {CNEISI}, year = {2011}, month = {09/2011}, address = {C{\'o}rdoba, Argentina}, author = {Abraham, L and Botta, A and Fratte, D and Oca{\~n}a, P} } @conference {93, title = {Speeding up the execution of a large number of statistical tests of independence}, booktitle = {Proceedings of ASAI 2010, Argentinean Symposioum of Artificial Intelligence}, year = {2010}, isbn = {978-950-9474-49-9}, author = {Schl{\"u}ter, Federico and Bromberg, Facundo and P{\'e}rez, Diego S} } @conference {80, title = {Strategies for piecing-together Local-to-Global Markov network learning algorithms}, booktitle = {ASAI 2011}, year = {2011}, month = {08/2011}, publisher = {Proceedings of ASAI 2011, Argentinean Symposioum of Artificial Intelligence}, organization = {Proceedings of ASAI 2011, Argentinean Symposioum of Artificial Intelligence}, address = {C{\'o}rdoba, Argentina}, author = {Schl{\"u}ter, F and Bromberg, F and Abraham, L} } @proceedings {225, title = {Sonda de temperatura para uso agr{\'\i}cola}, journal = {CASE Congreso Argentino de Sistemas Embebidos}, year = {2015}, edition = {2015}, issn = {978-987-45523-3-4}, author = {Guillermo Gr{\"u}nwaldt and Mat{\'\i}as Pecchia and Ana Laura Diedrichs and Germ{\'a}n Tabacchi and Gustavo Mercado} } @article {72, title = {A survey on independence-based Markov networks learning}, journal = {Artificial Intelligence Review}, volume = {42}, year = {2012}, month = {06/2012}, pages = {1093}, chapter = {1069}, abstract = {

The problem of learning\ the Markov network structure\ from data\ has become increasingly important in machine learning,
and in many other application fields.\ Markov networks are probabilistic graphical models,\ a widely used formalism for handling probability distributions in intelligent systems.\ This document focuses on a technology called \emph{independence-based} learning,\ which allows for the learning of the independence structure of Markov networks from data in an efficient and sound manner,\ whenever the dataset is sufficiently large, and data is a representative sample of the target distribution.\ In the analysis of such technology, this work surveys the current state-of-the-art algorithms,\ discussing its limitations, and posing a series of open problems\ where future work may produce some advances in the area, in terms of quality and efficiency.

}, keywords = {independence-based, Markov networks, Structure learning, survey}, issn = {1573-7462}, doi = {10.1007/s10462-012-9346-y}, url = {http://www.springerlink.com/content/e0l3113827341422}, author = {Federico Schl{\"u}ter} } @article {227, title = {SDCP: Streaming Distributed Control Protocol}, year = {2016}, url = {https://datatracker.ietf.org/doc/draft-perez-dispatch-sdcp/}, author = {Cristian Perez and Ana Laura Diedrichs} }