My articles and publications --(full text, click here. You may be asked to sign up --it is free) --Mis publicaciones (texto completo: http://ipn.academia.edu/AdolfoGuzman Quizá le pida suscribirse --es gratis) Mi página Web -- (click here) -- My Web page (http://alum.mit.edu/www/aguzman). ALGUNOS VIDEOS SOBRE LO QUE HAGO. Conferencia 'Ciudad inteligente, con conectividad y tecnología' (oct. 2010), parte 1 (15min), parte 2 (8min), parte 3 (9min), parte 4 (2min). Entrevista por redCudiMéxico, 2012: aquí (11 min). Avances en Inteligencia Artificial, entrevista en la Univ. IBERO, Puebla, 2013. Pulse aquí (53min). Video in the series "Personalities in the history of ESIME" (for the 100 years anniversary of ESIME-IPN, in Spanish) about Adolfo Guzman": 2014, click here. (1h)
Entrevista "La visión de los egresados del IPN, a 80 años de la creación del IPN y 100 años de la creación de la ESIME, 2014: ver en youtube (1h). Seminario sobre "Big Data" (la Ciencia de Datos). 2014. Pulse aquí (56min). Seminar on "Big Data", in English, 2014. Click here (56min). Algunos trabajos sobre Minería de Datos y sus Aplicaciones (CIC-IPN, 2016): pulse aquí (5min). El auge y el ocaso de las máquinas de Lisp (Plática en la Reunión Anual 2016 de la Academia Mexicana de Computación): pulse aquí (56min). Entrevista sobre la funcionalidad y competitividad de Hotware 10: 2016, aquí (6 min). Adolfo Guzmán Arenas, Ingeniero Electrónico e investigador del Centro de Investigación en Computación del IPN, conversó sobre su trayectoria y la importancia de las ciencias aplicadas para el desarrollo del país. 2017, Canal 11, Noticias TV (30min). Cómo se construyó la primera computadora en el mundo de procesamiento paralelo con Lisp. Marzo 2018. https://www.youtube.com/watch?v=dzyZGDhxwrU
(12 min).
Perfil en ResearchGate -- Adolfo Guzman-Arenas My URL in Google Scholar: http://scholar.google.com/citations?user=Nw5lSdEAAAAJ My ORCID number 0000-0002-8236-0469. Scopus Author ID 6602302516.

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Antecumen. Prototipo de herramienta para el análisis con cubos en memoria principal

184. Gilberto Martinez-Luna, Adolfo Guzmán-Arenas. (2008) Antecumen. Prototipo de herramienta para el análisis con cubos en memoria principal. Click here. Este artículo técnico fue publicado en la Conferencia Mundial sobre Tecnologías de la Informacion y Comunicaciones 2008.
Se describe una herramienta llamada Antecumem que se utiliza para desarrollar análisis en bases de datos almacenadas en memoria principal. La descripción abarca una lista de preguntas de negocio y el almacén de la base de datos. El almacén es una estructura de datos con arreglos y que están ligados entre sí, llamada Arblis, con lo cual no se buscan los datos en disco, lo que reduce el tiempo en la búsqueda de datos. Arblis almacena la base de datos, que es modelada como una base multi-dimensional (cubos de datos). Este modelo, permite definir operaciones con los cubos, operaciones con un interés sobre sucesos a través del tiempo, pero que también pueden ser en cualquier otra dimensión. Una operación con los datos de interés a analizar, puede ser el porcentaje de incremento de un período a otro. Arblis permite responder a la lista de preguntas de negocios aquí planteada.
(Technical paper). It describes a tool called Antecumem which is used for analysis in databases stored in main memory. The description includes a list of questions from business and store the database. The warehouse is a data structure and arrangements that are linked to each other, call Arblis, which does not seek data on disk, which reduces the time in the search for data. Arblis stores the database, which is modeled as a multi-dimensional (data cube). This model lets you define operations in the data cubes, oprations with an interest in events over time, but may also be in any other dimension. An operation with the data of interest to analyze, may be the percentage increase from one period to another. Arblis responding to the list of business questions raised here.

Ph. D. Thesis. A complete description of ANTECUMEN and Arblis is found in the Ph. D. Thesis of Gilberto Martinez, click here. Una descripción detallada de ANTECUMEN y Arblis, y programas accesorios, así como ejemplos y análisis teórico, se encuentra en la tesis de doctorado de Gilberto Martínez Luna. Abstract: This work deals with the design of a data structure called Arblis on main memory as a persistent warehouse only for reading, where to make searches and operations for data analysis. The design of the data structure helps to reduce the time to read the data of the main memory from 10 to 50 times, instead of reading them from disc, desirable reduction in information systems that make data analysis and decision support. The data stored is already validated and there is no modification process.
The data structure consists of two arrays linked between them. The data store is used by a software tool called Antecumem. The constructed tool full the data structure Arblis, captures the desired tasks, makes the corresponding data analyses and obtains the corresponding results.
The tasks of data analysis are on businesses questions that work with data range in different variables that have a special interest. In order to obtain the answer of the businesses questions it is generally required to merge thousands and sometimes millions of records. Besides, the processes are expensive by the access to the data, and also, they are expensive in the number of operations between the records.
The data ranges in the variables define to the tool to have like work unit the multi-dimensional model or the datacube. This unit allows to define operations on the results of analyzing the datacubes. The operations are union, intersection and difference. In general these are of interest in events through time, but it may be in any dimension. In addition, it allows to define operations on the facts, like the percentage of increase from a period to another one.
With the identification of the key elements (parameters and datacube) of the businesses questions when making a classification of them, obtained a work model in order to facilitate the creation of the corresponding algorithms to solve the questions. This model allows to see the base as a multi-dimensional database. The flexibility of the model allows to answer more business questions which were not consider of the start.
Based in the model, the tool uses an input screen to receive the parameters that define the type of businesses question, to accept the ranks of data to define the datacubes where the questions are answered and the corresponding screen to return the results for an interpretation of the results.
As a further proof of the usefulness of the data structure, Antecumem is used to model to the nodes of a called structure lattice. Lattice stores the views that form or complement to the datacube. This structure allows according to the ranks of the question, to select the detail of records or to make the decision to directly go to read the already accumulated records within the nodes of latice. It is decision helps to reduce plus the response time, in other types of questions, in addition to the modeled ones initially.
Palabras claves. Bases de Datos Relacionales, Cubo en Memoria, Datos en Memoria, Minería de Datos, Minería Incremental, Ajuste de Curvas, Bases de Datos Multidimensionales, OLAP, Cubos de Datos y Lattices.

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