ABSTRACT. In order to guarantee the security of transactions through the Internet and to generate strong evidence that could be used in the future in case of legal disputes, several countries around the world have promoted and regulated the use of digital signatures based on the Public Key Infrastructure (PKI). However, despite the high expectations, its implementation has achieved neither the desired results nor its global massification. Many of thereasonshave been discovered years ago, but they are still been open problems for the scientific community nowadays. In order to consider the case of the national PKI of the Peruvian state, as empirical evidence, in studies that address the open problems, this article describes the details about a new certification hierarchy which is expected to overcome some of theof its predecessors’limitations. It is also expected that the information disclosed in this articlecouldbe useful to other countries formaking a preliminary assessment for possible cross-border recognition of Peruvian digital signatures

ABSTRACT. TBD

ABSTRACT. In organizations, the Enterprise Architecture (AE) represents both business and Information Technology (IT) perspective, which must be constantly updated in response to the transformations of the company, difficult to achieve. The problem has been addressed on different fronts and there are still ways to explore, one of them is the Blockchain technology, especially the way to extend the logic of smart contracts to the company. It is proposed to implement activities of operational processes through smart contracts, which could detect that, the process in which they are operating, has an unexpected behavior and, in turn, warn of possible needs to update the AE and the same smart contract.

ABSTRACT. En este artículo se presenta uno de los resultados del proyecto de investigación cuyo objetivo fue detectar patrones de desempeño académico en las competencias genéricas de los estudiantes colombianos de carreras profesionales que presentaron las Pruebas de Estado Saber Pro, a partir de los datos socioeconómicos, académicos e institucionales almacenados en las bases de datos del ICFES, utilizando técnicas de minería de datos. Se aplicó CRISP-DM como metodología por ser la guía de referencia más ampliamente utilizada en proyectos de minería de datos. Para la competencia de comunicación escrita se construyó, limpió y transformó un repositorio de datos con los resultados de las pruebas Saber Pro que presentaron los estudiantes entre los años 2012 y 2014. Este repositorio se restringió a los estudiantes de carreras afines a la Computación y se le aplicó la técnica de de clasificación por árboles de decisión. Entre los patrones descubiertos en esta competencia, la acreditación institucional se encuentra asociada con otros factores, tanto al buen como al mal desempeño académico. El conocimiento descubierto se incorporará al existente y podrá ser utilizado en los procesos de toma de decisiones del ICFES y de las instituciones gubernamentales y académicas que velan por la calidad de la educación superior.

ABSTRACT. Emotion detection is crucial in Human-Computer Interaction (HCI). Computers can never respond to individuals affective state if it cannot identify its emotion. Categorical approaches are commonly used for emotion detection in texts. It considers training models based on a set of affective states. Categorical approaches are often based on a dictionary that contains words associated with emotional categories. In this scenario, LIWC dictionaries have been widely used in psychology and linguistics. There are dictionaries in many languages, including Brazilian Portuguese (LIWC2007pt). This work focuses on the development of AffectPT-br, a new Brazilian Portuguese affective dictionary based on the LIWC 2015 English dictionary. We produced two text classification experiments with real datasets from social networks in order to compare AffectPT-br with LIWC2007pt. Results indicate AffectPT-br outperforms LIWC2007pt in the classification task with all classification algorithms we adopted.

ABSTRACT. Latent Dirichlet Allocation (LDA) is a fundamental method in the text mining field. We propose strategies for topic and model selection based on LDA that exploits the semantic coherence of the topics inferred, boosting the quality of the models found. Then we study how our boosted topic models perform in ad-hoc information retrieval tasks. Experimental results in four datasets show that our proposal improves the quality of the topics found favoring document retrieval tasks. Our method outperforms traditional LDA-based methods showing that model selection based on semantic coherence is useful for document modeling and information retrieval tasks.

ABSTRACT. Ecuador is located at the collision point of two tectonic plates: Nazca and South America, an area with high seismic activity; hence it is common that a large number of seismic events occur annually. On April 16, 2016, a Mw 7.8 earthquake impacted coastal Ecuador, and as frequently happens after large earthquakes take place, a large number of aftershocks were located within the affected and surrounding areas. Determining similar seismic geographical zones of the such events has become a problem of great interest for postearthquake mitigation actions. In this paper, we present an approach to cluster seismic events in the areas affected by the Mw 7.8 Ecuador earthquake for the past two years. The seismic events data are obtained from permanent stations at the Geophysical Institute of the National Polytechnic School (IGEPN) installed throughout the country. We carried out unsupervised pattern recognition through a graph-based clustering algorithm called MST-kNN which determines number of cluster k automatically. The geographical clustering was carried out successfully using spatial location coordinates of latitude and longitude of every seismic event. Our approach identified five clusters with similar seismic geographic distribution along provinces of Esmeraldas, Manabí, Santa Elena and their coasts in the Pacific Ocean. The results can be used by governments to plan post-earthquake mitigation strategies of future strong seismic events such as identifying safe roads for evacuation plans in case of posible tsunamis or adequate location of adhoc health and supply centers.

ABSTRACT. Octree–based algorithms recursively divide the space in 8 or 27 hexahedra (octants). The number of times the split process is applied over an octant is the Refinement Level (RL). When a mesh presents octants of different RL, it is required to manage the transition between fine and coarse regions of the mesh. To do this, transition patterns are applied over octants with neighbors of different RL. When using the 27–split process this can be done only using hexahedra, however in the case of 8–split process this must be done using different types of elements (mixed–elements). The validity of the elements in the transition is ensured when the octant is a regular hexahedron. However, this may not be true when the octant is at the boundary of the domain, specially in concave regions. In this work we introduce a novel node projection technique in order to repair the boundary elements of transition regions in the mesh. Tests results show that, in general, invalid elements can be eliminated without impacting adjacent elements.

ABSTRACT. This paper presents a variant of Snay's algorithm for profile reduction of matrices. The new heuristic for profile reduction shows better results when compared with the results of several reordering algorithms with regards to reducing the computational cost of the zero-fill incomplete Cholesky-preconditioned conjugate gradient method applied to small linear systems arising from a computational fluid dynamics problem.