Ingeniería Informática

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Aggregation languages for moving object and places of interest
(2008) Gómez, Leticia Irene; Kuijpers, Bart; Vaisman, Alejandro Ariel
"We address aggregate queries over GIS data and moving object data, where non-spatial information is stored in a data warehouse. We propose a formal data model and query language to express complex aggregate queries. Next, we study the compression of trajectory data, produced by moving objects, using the notions of stops and moves. We show that stops and moves are expressible in our query language and we consider a fragment of this language, consisting of regular expressions to talk about temporally ordered sequences of stops and moves. This fragment can be used not only for querying, but also for expressing data mining and pattern matching tasks over trajectory data."
AirFitness: generación de rutinas personalizadas con IA y corrección de ejercicios con ML
(2020-12) Kramer, Esteban; Scomazzon, Martina; Dolagaratz, Gonzalo
"AirFitness busca facilitar el proceso de realizar ejercicio físico y estar en forma sin la necesidad de ir a un gimnasio o tener un entrenador personal."
An algebra for OLAP
(2017) Kuijpers, Bart; Vaisman, Alejandro Ariel
"Online Analytical Processing (OLAP) comprises tools and algorithms that allow querying multidimensional databases. It is based on the multidimensional model, where data can be seen as a cube, where each cell contains one or more measures can be aggregated along dimensions. Despite the extensive corpus of work in the field, a standard language for OLAP is still needed, since there is no well-defined, accepted semantics, for many of the usual OLAP operations. In this paper, we address this problem, and present a set of operations for manipulating a data cube. We clearly define the semantics of these operations, and prove that they can be composed, yielding a language powerful enough to express complex OLAP queries. We express these operations as a sequence of atomic transformations over a fixed multidimensional matrix, whose cells contain a sequence of measures. Each atomic transformation produces a new measure. When a sequence of transformations defines an OLAP operation, a flag is produced indicating which cells must be considered as input for the next operation. In this way, an elegant algebra is defined. Our main contribution, with respect to other similar efforts in the field is that, for the first time, a formal proof of the correctness of the operations is given, thus providing a clear semantics for them. We believe the present work will serve as a basis to build more solid practical tools for data analysis."
Análisis automático del rendimiento de los jugadores en partidos de tenis
(2020) Izaguirre, Agustín Emilio; Gambini, Juliana
"El problema de seguimiento de objetos en secuencias de imágenes y en videos tiene múltiples aplicaciones en distintos aspectos, como el estudio del medio ambiente, el estudio del comportamiento de animales, la robótica, la seguridad y el diagnóstico médico, entre otras. Una de las aplicaciones que posee el seguimiento de objetos, que se desarrolló en los últimos años, es la posibilidad de detectar acciones en eventos deportivos, en tiempo real, lo que resulta muy útil para colaborar en la tarea del árbitro y también para analizar el rendimiento de los jugadores. Los diferentes eventos deportivos donde se pueden utilizar son eventos de fútbol, vóley, handball, etc. En este trabajo, se aplica un método de seguimiento de objetos en secuencias de imágenes para detectar resultados de jugadas en partidos de tenis y realizar un análisis estadístico del rendimiento deportivo de cada jugador."
Análisis de datos de pacientes y consultantes con COVID-19
(2021-09-29) Pingarilho, Pedro Remigio; Gómez, Fermín; Di Luca, Miguel; Gambini, Juliana
Análisis de imágenes de microscopía
(2021-08-24) Della Sala, Rocío; Rodríguez, Ariel Andrés; Bruno, Luciana; Gambini, Juliana
"El análisis automático de imágenes tiene múltiples campos de aplicación, siendo uno de estos el análisis a nivel celular donde se estudian imágenes microscópicas. En el presente trabajo se implementan métodos para poder extraer tanto información cuantitativa como también cualitativa de una serie de películas de distintos citoesqueletos. El objetivo es construir una herramienta que facilite el estudio de imágenes y nos permita obtener información que no se podría extraer a simple vista. El trabajo se centra en el estudio de 3 propiedades las cuales son el contorno de la estructura del citoesqueleto, el movimiento de la estructura a lo largo de la película y la textura en distintas zonas de la imagen. Para cada una de estas propiedades se desarrollan múltiples métodos y se opta por elegir aquellos que presenten los mejores resultados en el menor tiempo posible, teniendo en cuenta que su funcionamiento sea independiente de la forma de los citoesqueletos o de la intensidad de cada imagen. Si bien este estudio presenta dificultades como el ruido en este tipo de imágenes o la diversidad de las estructuras de los citoesqueletos, para todas las propiedades se logran obtener interesantes resultados."
Análisis de sentimiento: comparación de algoritmos predictivos y métodos utilizando un lexicon español
(2019-07-29) Pauli, Pablo Agustín; Soliani, Valeria
"El propósito de este proyecto es por un lado realizar una comparación entre distintos algoritmos de aprendizaje supervisado y ver que tan confiables son a la hora de clasificar la información luego de pasarlos por un proceso de entrenamiento."
Analysing river systems with time series data using path queries in graph databases
(2023) Bollen, Erik; Hendrix, Rik; Kuijpers, Bart; Soliani, Valeria; Vaisman, Alejandro
Transportation networks are used in many application areas, like traffic control or river monitoring. For this purpose, sensors are placed in strategic points in the network and they send their data to a central location for storage, viewing and analysis. Recent work proposed graph databases to represent transportation networks, since these networks can change over time, a temporal graph data model is required to keep track of these changes. In this model, time-series data are represented as properties of nodes in the network, and nodes and edges are timestamped with their validity intervals. In this paper, we show that transportation networks can be represented and queried using temporal graph databases and temporal graph query languages. Many interesting situations can be captured by the temporal paths supported by this model. To achieve the above, we extend a recently introduced temporal graph data model and its high-level query language T-GQL to support time series in the nodes of the graph, redefine temporal paths and study and implement new kinds of paths, namely Flow paths and Backwards Flow paths. Further, we analyze a real-world case, using a portion of the Yser river in the Flanders’ river system in Belgium, where some nodes are equipped with sensors while other ones are not. We model this river as a temporal graph, implement it using real data provided by the sensors, and discover interesting temporal paths based on the electric conductivity parameter, that can be used in a decision support environment, by experts for analyzing water quality across time.
Analysis of invariants for efficient bounded verification
(2010-07) Galeotti, Juan Pablo; Rosner, Nicolás; López Pombo, Carlos G.; Frías, Marcelo
"SAT-based bounded veri cation of annotated code consists of translating the code together with the annotations to a propositional formula, and analyzing the formula for speci cation violations using a SAT-solver. If a violation is found, an execution trace exposing the error is exhibited. Code involving linked data structures with intricate invariants is particularly hard to analyze using these techniques. In this article we present TACO, a prototype tool which implements a novel, general and fully automated technique for the SAT-based analysis of JML-annotated Java sequential programs dealing with complex linked data structures. We instrument code analysis with a symmetry-breaking predicate that allows for the parallel, automated computation of tight bounds for Java elds. Experiments show that the translations to propositional formulas require signi cantly less propositional variables, leading in the experiments we have carried out to an improvement on the e ciency of the analysis of orders of magnitude, compared to the non instrumented SAT-based analysis. We show that, in somecases, our tool can uncover bugs that cannot be detected by state-of-the-art tools based on SAT-solving, model checking or SMT-solving."
An analysis of public transport in the city of Buenos Aires with MobilityDB
(2020-01-25) Godfrid, Juan; Radnic, Pablo; Vaisman, Alejandro Ariel; Zimányi, Esteban
"The General Transit Feed Specication (GTFS) is a data format used to express public transportation schedules and associated geographic information created in 2006 by Google. It is now widely used all around the world in both of its versions, GTFS Real-Time and GTFS Static. So far, tools to analyze these data are not widely available in the open source community. Companies that need to perform in-depth analysis must create proprietary solutions which the public has no access to. MobilityDB is a free and open source PostgreSQL and PostGIS extension that adds spatial and temporal datatypes along with convenient functions, to facilitate the analysis of mobility data. However, loading GTFS data into MobilityDB must still be done in an ad-hoc fashion. Furthermore, obtaining GTFS real-time data is an even more involved problem. This work describes how MobilityDB is used to analyze public transport mobility in the city of Buenos Aires. To this end, static and real-time GTFS data for the Buenos Aires public transportation system were acquired, imported into MobilityDB, and analyzed. Visualizations were also produced to enhance the analysis."
An analysis of the suitability of test-based patch acceptance criteria
(2017-07) Zemín, Luciano; Gutiérrez Brida, Simón; Godio, Ariel; Cornejo, César; Degiovanni, Renzo; Regis, Germán; Aguirre, Nazareno; Frías, Marcelo
"Program repair techniques attempt to fix programs by looking for patches within a search space of fix candidates. These techniques require a specification of the program to be repaired, used as an acceptance criterion for fix candidates, that often also plays an important role in guiding some search processes. Most tools use tests as specifications, which constitutes a risk, since the incompleteness of tests as specifications may lead one to obtain spurious repairs, that pass all tests but are in fact incorrect. This problem has been identified by various researchers, raising concerns about the validity of program fixes. More thorough studies have been proposed using different sets of tests for fix validation, and resorting to manual inspection, showing that while tools reduce their program fixing rate, they are still able to repair a significant number of cases. In this paper, we perform a different analysis of the suitability of tests as acceptance criteria for automated program fixes, by checking patches produced by automated repair tools using a bug-finding tool, as opposed to previous works that used tests or manual inspections. We develop a number of experiments in which faulty programs from a known benchmark are fed to the program repair tools GenProg, Angelix, AutoFix and Nopol, using test suites of varying quality and extension, including those accompanying the benchmark. We then check the produced patches against formal specifications using a bug-finding tool. Our results show that, in general, automated program repair tools are significantly more likely to accept a spurious program fix than producing an actual one, in the studied scenarios. "
Analytical queries on semantic trajectories using graph databases
(2019-10) Gómez, Leticia Irene; Kuijpers, Bart; Vaisman, Alejandro Ariel
"This article studies the analysis of moving object data collected by location-aware devices, such as GPS, using graph databases. Such raw trajectories can be transformed into so-called semantic trajectories, which are sequences of stops that occur at “places of interest.” Trajectory data analysis can be enriched if spatial and non-spatial contextual data associated with the moving objects are taken into account, and aggregation of trajectory data can reveal hidden patterns within such data. When trajectory data are stored in relational databases, there is an “impedance mismatch” between the representation and storage models. Graphs in which the nodes and edges are annotated with properties are gaining increasing interest to model a variety of networks. Therefore, this article proposes the use of graph databases (Neo4j in this case) to represent and store trajectory data, which can thus be analyzed at different aggregation levels using graph query languages (Cypher, for Neo4j). Through a real-world public data case study, the article shows that trajectory queries are expressed more naturally on the graph-based representation than over the relational alternative, and perform better in many typical cases."
Analyzing public transport in the city of Buenos Aires with MobilityDB
(2022) Godfrid, Juan; Radnic, Pablo; Vaisman, Alejandro Ariel; Zimányi, Esteban
"The General Transit Feed Specification (GTFS) is a data format widely used to share data about public transportation schedules and associated geographic information. GTFS comes in two versions: GTFS Static describing the planned itineraries and GTFS Realtime describing the actual ones. MobilityDB is a novel and free open-source moving object database, developed as a PostgreSQL and PostGIS extension, that adds spatial and temporal data types along with a large number of functions, that facilitate the analysis of mobility data. Loading GTFS data into MobilityDB is a quite complex task that, nevertheless, must be done in an ad-hoc fashion. This work describes how MobilityDB is used to analyze public transport mobility in the city of Buenos Aires, using both, static and real-time GTFS data for the Buenos Aires public transportation system. Visualizations are also produced to enhance the analy-sis. To the authors’ knowledge, this is the first attempt to analyze GTFS data with a moving object database."
Analyzing the quality of Twitter data streams
(2022) Arolfo, Franco; Cortés Rodriguez, Kevin; Vaisman, Alejandro Ariel
"There is a general belief that the quality of Twitter data streams is generally low and unpredictable, making, in some way, unreliable to take decisions based on such data. The work presented here addresses this problem from a Data Quality (DQ) perspective, adapting the traditional methods used in relational databases, based on quality dimensions and metrics, to capture the characteristics of Twitter data streams in particular, and of Big Data in a more general sense. Therefore, as a first contribution, this paper re-defines the classic DQ dimensions and metrics for the scenario under study. Second, the paper introduces a software tool that allows capturing Twitter data streams in real time, computing their DQ and displaying the results through a wide variety of graphics. As a third contribution of this paper, using the aforementioned machinery, a thorough analysis of the DQ of Twitter streams is performed, based on four dimensions: Readability, Completeness, Usefulness, and Trustworthiness. These dimensions are studied for several different cases, namely unfiltered data streams, data streams filtered using a collection of keywords, and classifying tweets referring to different topics, studying the DQ for each topic. Further, although it is well known that the number of geolocalized tweets is very low, the paper studies the DQ of tweets with respect to the place from where they are posted. Last but not least, the tool allows changing the weights of each quality dimension considered in the computation of the overall data quality of a tweet. This allows defining weights that fit different analysis contexts and/or different user profiles. Interestingly, this study reveals that the quality of Twitter streams is higher than what would have been expected."
Analyzing the quality of Twitter data streams
(2020) Arolfo, Franco A.; Cortes Rodriguez, Kevin; Vaisman, Alejandro Ariel
"There is a general belief that the quality of Twitter data streams is generally low and unpredictable, making, in some way, unreliable to take decisions based on such data. The work presented here addresses this problem from a Data Quality (DQ) perspective, adapting the traditional methods used in relational databases, based on quality dimensions and metrics, to capture the characteristics of Twitter data streams in particular, and of Big Data in a more general sense. Therefore, as a first contribution, this paper re-defines the classic DQ dimensions and metrics for the scenario under study. Second, the paper introduces a software tool that allows capturing Twitter data streams in real time, computing their DQ and displaying the results through a wide variety of graphics. As a third contribution of this paper, using the aforementioned machinery, a thorough analysis of the DQ of Twitter streams is performed, based on four dimensions: Readability, Completeness, Usefulness, and Trustworthiness. These dimensions are studied for several different cases, namely unfiltered data streams, data streams filtered using a collection of keywords, and classifying tweets referring to different topics, studying the DQ for each topic. Further, although it is well known that the number of geolocalized tweets is very low, the paper studies the DQ of tweets with respect to the place from where they are posted. Last but not least, the tool allows changing the weights of each quality dimension considered in the computation of the overall data quality of a tweet. This allows defining weights that fit different analysis contexts and/or different user profiles. Interestingly, this study reveals that the quality of Twitter streams is higher than what would have been expected."
AntSwarm
(2012) Goldberg, Daniel; Liendro, José Indalecio; Parisi, Daniel
"El objetivo general del presente trabajo final es aplicar y desarrollar las herramientas de procesamiento de imágenes y video necesarias para poder analizar los registros adquiridos en los experimentos particulares."
Aprendizaje por refuerzo con opciones y función de refuerzo universal
(2020-12) Bruno Cilla, Diego; Heimann, Matías; Scaglioni, Giuliano; Santos, Juan Miguel
"El objetivo de los algoritmos de aprendizaje por refuerzo es maximizar las recompensas acumuladas a lo largo del tiempo para hallar un comportamiento objetivo. De esta forma, para aprender distintos comportamientos, la variable a cambiar sería la función de refuerzo dada para ese problema. El objetivo de este trabajo es explorar una alternativa en la cual se puedan adquirir distintos comportamientos, manteniendo siempre la misma función de refuerzo, siendo que la variable sea los distintos entornos en los que se realiza el aprendizaje."
ATR: Template-based repair for alloy specifications
(2022) Zheng, Guolong; Vu Nguyen, Thanh; Gutiérrez Brida, Simón; Regis, Germán; Aguirre, Nazareno; Frías, Marcelo F.; Bagheri, Hamid
"Automatic Program Repair (APR) is a practical research topic that studies techniques to automatically repair programs to fix bugs. Most existing APR techniques are designed for imperative programming languages, such as C and Java, and rely on analyzing correct and incorrect executions of programs to identify and repair suspicious statements. We introduce a new APR approach for software specifications written in the Alloy declarative language, where specifications are not “executed”, but rather converted into logical formulas and analyzed using backend constraint solvers, to find specification instances and counterexamples to assertions. We present ATR, a technique that takes as input an Alloy specification with some violated assertion and returns a repaired specification that satisfies the assertion. The key ideas are (i) analyzing the differences between counterexamples that do not satisfy the assertion and instances that do satisfy the assertion to guide the repair and (ii) generating repair candidates from specific templates and pruning the space of repair candidates using the counterexamples and satisfying instances. Experimental results using existing large Alloy benchmarks show that ATR is effective in generating difficult repairs. ATR repairs 66.3% of 1974 fault specifications, including specification repairs that cannot be handled by existing Alloy repair techniques."
Autoenconders y análisis de componentes principales: propuesta de generación de ejemplos adversarios en el contexto de sistemas de reconocimiento facial
(2021-10-11) Fuster, Marina; Vidaurreta, Ignacio Matías; Pierri, Alan
"En el presente trabajo se propone una nueva metodología de generación de ejemplos adversarios, datos manipulados para confundir algoritmos de clasificación. El objetivo en este caso es vulnerar sistemas de reconocimiento facial con una estrategia que se basa en el uso de autoencoders, un tipo de redes neuronales, y análisis de componentes principales."
Automated detection of facial expressions using image analysis
(2019-07-05) Casagrande, Lucas; Kuyumciyan, Nicolás; Gambini, Juliana
"The broad range of applications for automatic expression detection sparks the need for a robust and effective implementation. In this paper, an exposition of the existing methods most frequently used for this purpose is done, and an analysis of their performance is carried out. These include both feature detection methods such as Gabor filters and Histograms of Gradients as well as classifiers based in neural networks. Existing data sets consisting of images of persons faces with a labeled expression are used for training and testing purposes. A success rate of 87.6% is achieved when classifying images with up to four different expressions."

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