The Role of Interactive Digital Resources in Mathematics Education and Research
By: José Luis Abreu León
Fue profesor en la Facultad de Ciencias de la UNAM (Universidad Nacional Autónoma de México), miembro fundador del CIMAT (Centro de Investigación en Matemáticas), en Guanajuato México, investigador y director del IIMAS (Instituto de Investigación en Matemáticas Aplicadas y Sistemas) de la UNAM, profesionista autónomo en España especializado en el desarrollo de software educativo, director técnico del proyecto MALTED de la Comisión Europea, y director de desarrollo Tecnológico en el Instituto Latinoamericano de la Comunicación Educativa. Fundador del LITE (Laboratorio de Innovación en Tecnología Educativa). Actualmente es técnico académico en el Instituto de Matemáticas de la UNAM y Director del LITE. Creador de DESCARTES herramienta con la que se producen contenidos educativos interactivos de matemáticas y física en España, México y otros países. Sus intereses son el desarrollo de herramientas de autor para la creación de contenidos interactivos digitales, y su publicación en WEB para apoyo de la enseñanza, la difusión y la investigación.
Examples will be shown of interactive educational resources created for Math education. Also some resources developed during the course of mathematical research, will be shown and their genesis will be explained. From these examples an analysis will be made of the role of digital interactive resources in Math education and research. What aspects of education may be addressed with interactive resources? What aspects of Math research may take advantage of interactive resources? Finally, best practices for the production of interactive resources for education will be analysed.
Design of Analog Integrated Circuits in submicrometer technologies
By: Jaime Ramírez Angulo
Jaime Ramírez-Angulo is currently Klipsch Distinguished Professor, IEEE Fellow, and Director of the Mixed-Signal VLSI Lab at the Klipsch School of Electrical and Computer Engineering, New Mexico State University ( Las Cruces, New Mexico), USA. He received a degree in Communications and Electronic Engineering (Professional degree), a M.S.E.E. from the National Polytechnic Institute in Mexico City and a Dr.-Ing degree form the University of Stuttgart in Stuttgart, Germany in 1974, 1976 and 1982 respectively. He was professor at the National Institute for Astrophysics Optics and Electronics (INAOE) and at Texas A&M University. His research is related to various aspects of design and test of analog and mixed-signal Very Large Scale Integrated Circuits. He has made numerous contributions to this field which have been reported in over four hundred sixty publications in the most prestigious journals and conferences in analog circuit design. He has two high technology patents and has held numerous invited and keynote presentations. He has been a consultant to Texas Instruments, NASA-ACE, NASA-Ames, NASA Goddard and Oak Ridge National Laboratories. His research has been supported by National Science Foundation, Sandia National Labs, Los Alamos National Labs, Engineering Foundation, Texas Instruments and Agilent. He received the prestigious URC University Research Council for exceptional achievements in creative scholarly activities and the Westhafer award for Excellence in Research and Creativity in March and May 2002 respectively. The Westhafer award is the highest faculty award for research merits at New Mexico State University. On October 2002 he was named Paul W. Klipsch Distinguished Professor and was IEEE distinguished lecturer for the period 2003-2005. Two of his papers were listed in 2005 among the 100 most downloaded papers of all IEEE societies. In May 2004 one of his students earned the award as most outstanding Ph.D student and in 2006 and 2007 two of his students earned the award as most outstanding M.Sc. students at New Mexico State University. He was a Fulbright scholar for the period September 2009-May 2010 and was in the IEEE Circuits and Systems Fellow Selection Committee in 2009.
Challenges faced by analog designers in modern deep submicrometer CMOS technologies are discussed: a) Drastically reduced supply voltages (currently single supplies close to 1V) with comparable transistor threshold Voltages (in the order of 0.4V). This restriction leads to small signal swing and does not allow utilization of classical analog architectures that stack more than two transistors, b) Low transistor gain gmro (on the order of 10-20) caused by increased channel length modulation, c) High gate and drain Transistor leakage, d) Poor transconductance parameters of PMOS Transistors relative to NMOS transistors. As illustrative example a comparative study of conventional op-amp architectures in CMOS technologies with feature sizes ranging from 130nm to 65nm is made to show degradation of analog performance as technology evolves. We introduce then several approaches to overcome the limitations imposed by modern CMOS technology. Among these approaches we discuss several techniques to achieve high gain, rail to rail swing, for power efficient class AB operation even with subvolt supplies
Probabilistic reasoning in answer set programming — the P-log approach
By: Michael Gelfond
Dr. Michael Gelfond was born on November 7, 1945 in the city of Leningrand (now St. Petersburg), Russia. He received an M. D in Mathematics from St. Petersburg University in 1968. He got a Ph. D. in Mathematics from Steklov Mathematical Institute, St Petersburg, Russia, in 1974. Currently, Dr. Gelfond is a professor of Computer Science at Texas Tech University, Texas, USA. Dr. Gelfond has been mainly interested in the development of formal mechanisms for representing commonsense knowledge and the study if their mathematical and computational properties. His main contributions have been done in the contest of nonmonotonic reasoning. In particular, he has defined significant results in the area of logic programming semantics with negation as failure. The paper “The Stable Model Semantics for Logic Programs” (co-authored with Vladimir Lifschitz ) is perhaps one of his main achievements to date. This paper has received the Most Influential Paper in 20 Years Award from the Association for Logic Programming in 2004. On the other hand, the results of this paper defined the key stone of a new logic programming paradigm which is called “Answer Set Programming (ASP)”. Dr Gelfond has also introduced important contributions in the representation of actions and their effects in the context of dynamic systems. Indeed, He contributed in the implementation of a practical industrial-sized application of ASP-based planning for NASA on the Reaction Control System of the Space Shuttle. Dr. Gelfond has been elected as a Fellow of the American Association from Artificial Intelligence and member of the European Academy of Science. He is editor of the Journal of Theory and Practice of Logic Programming in the area of Knowledge Representation and Nonmonotonic Reasoning. He is also an executive editor of the Journal of Logic and Computation. He is a co-organizer of the Texas Action Group. He is a co-found and co-head of the Knowledge Representation Lab at Texas Tech University. In 2011, the book “Logic Programming Knowledge Representation and Nonmonotonic Reasoning, Lecture Notes in Computer Science 6565 Springer 2011, ISBN 978-3-642-20831-7” was dedicated to Dr. Gelfond on the occasion of his 65th birthday.
In this talk I present a short introduction to the knowledge representation language P-log. The language, designed by C. Baral, M. Gelfond, and N. Rushton was supposed to
(1) allow elegant and elaboration tolerant formalization of non-trivial combinations of logical
and probabilistic reasoning,
(2) help the language designers (and hopefully others) to better understand the meaning of probability and probabilistic reasoning,
(3) better understand how to build and implement knowledge based software systems.
The logical framework of P-log is Answer Set Prolog and its extensions– powerful non-monotonic formalisms designed to represent and reason about beliefs of rational agent. On the probabilistic side the authors adopt the view according to which probabilistic reasoning is common sense reasoning about degrees of belief of a rational agent. Probabilistic foundations of P-log are causal Bayesian nets. In addition to sets of possible beliefs of a rational agent defined by answer sets of a P-log program this program also defines the probability function on the set of such possible worlds.
There are several other distinctive features of P-log. First, P-log probabilities are defined with respect to explicitly stated knowledge base. This allows explicitly specify the agent’s background knowledge which is normally “hidden” in classical approach to probability. Second, P-log is probabilistically non-monotonic — addition of new information can add new possible worlds and substantially change the original probabilistic model. Third, in addition to updates of its knowledge base by new facts, P-log allows updates to be defaults, rules containing terms not belonging to the original language, and deliberate actions in the sense of Judea Pearl. Some of these features will be discussed and illustrated by informal examples.
By: Luis Enrique Sucar
L. Enrique Sucar has a Ph.D in computing from Imperial College, London, UK, 1992; a M.Sc. in electrical engineering from Stanford University, California, USA, 1982; and a B.Sc. in electronics and communications engineering from ITESM, Monterrey, Mexico, 1980. He has been a Researcher at the Electrical Research Institute and Professor at ITESM Cuernavaca, and is currently Director of Research at INAOE, Puebla, Mexico. He has been an invited professor at the University of British Columbia, Canada; Imperial College, London; and INRIA, France. He has more than 150 publications in journals and conference proceedings, and has directed 16 Ph.D. thesis. Dr. Sucar is Member of the National Research System, the Mexican Science Academy, and Senior Member of the IEEE. He has served as president of the Mexican AI Society, has been member of the Advisory Board of IJCAI, and is Associate Editor of the journals Computación y Sistemas and Revista Iberoamericana de Inteligencia Artificial. His main research interest are in graphical models and
probabilistic reasoning, and their applications in computer vision, robotics and biomedicine.
Robots are coming out of industry and laboratories to help us in daily life activities; a new generation of robots are being developed named “Service Robots”. Service robots require new capacities, such as navigating in complex and dynamic environments, communicating with people in a natural way, manipulating objects, among others. In this talk I will present our service robot, “Markovito”, and discuss several of its main capabilities, such as map building, navigation and
localization; person detection and recognition; interaction via voice and gestures; etc. To perform a task, Markovito combines its capabilities which are coordinated by a decision-theoretic controller. We will talk about some of the tasks that Markovito can perform in the context of the RoboCup@Home competition, including serving beers to its costumers!