IEEE Argentina tiene el agrado de informarle sobre las próximas actividades a realizarse durante el mes de Septiembre 2004. Esperamos que sean de su interés y contar con su grata presencia en ellas.


CURSOS

* IEEE Signal Processing Society - Capítulo Argentino
Curso SP02: “Introducción al Procesamiento Digital de Señales"
Conductores: Ing. Daniel Jacoby e Ing. Roxana Saint-Nom
Martes 7, Jueves 9, Martes 14 y Jueves 16 de septiembre, de 18:30 a 21:30
Auditorio de IEEE / CICOMRA. Buenos Aires.


* IEEE Signal Processing Society - Capítulo Argentino
Curso SP03: “Aplicaciones con Procesadores Digitales de Señales"
Conductores: Ing. Daniel Jacoby e Ing. Roxana Saint-Nom
Martes 5, Jueves 7, Martes 12 y Jueves 14 de octubre, de 18:30 a 21:30
Auditorio de IEEE / CICOMRA. Buenos Aires.

 


PROGRAMA DE CONFERENCISTAS DISTINGUIDOS

* IEEE Computer Society - Capítulo Argentino
Conferencias y Tutorial del Dr. Jaideep Srivastava

Conferencia: Web Mining
Lunes 20 de septiembre, 18:30, Universidad CAECE (Buenos Aires)

Conferencia: Data Mining for Computer Security
Miercoles 22 de septiembre, 10:30, Facultad de Ingenieria UBA (Buenos Aires)

Tutorial: Web Mining Accomplishments and Future Directions
ExpoComm.
Para inscripcion en este Tutorial: http://www.expocomm.com.ar



Para inscripción en los Cursos y las Conferencias dirigirse a la sede de IEEE / CICOMRA:
Tel: (011) 4325-8839
Fax: (011) 4325-9604
E-mail: sec.argentina@ieee.org
Av. Córdoba 744, 2º Piso 'D', C1054AAT Buenos Aires - Argentina

Las conferencias no son aranceladas, pero agradeceremos inscribirse a las mismas anticipadamente.

 


DETALLE DE LAS ACTIVIDADES

IEEE Signal Processing Society- Capítulo Argentino
Curso SP02: “Introducción al Procesamiento Digital de Señales"

Objetivo
Proporcionar un camino sencillo y probado para iniciarse en esta área de la ingeniería electrónica, que requiere de habilidades matemáticas avanzadas pero que su vez proporciona un gran campo de aplicación práctica.

Dirigido a
Profesionales en el área de la ingeniería, la informática y las ciencias que buscan tener una sólida base para manejarse en el área de procesamiento digital de señales.

Temario
1. Muestreo de señales analógicas
2. Señales y sistemas discretos
3. Transformada Z y sus aplicaciones
4. La transformada discreta de Fourier
5. La transformada rápida de Fourier
6. Diseño básico de filtros digitales
7. Aplicaciones
8. Conceptos de Hardware y Software de DSP
9. Demostraciones

Conductores
Ing. Daniel Jacoby . Ingeniero Electrónico ITBA. Profesor Titular en el ITBA.
Ing. Roxana Saint-Nom . Ingeniera Electrónica ITBA. Profesora titular e investigadora en el ITBA.

Fecha y lugar de realización
Martes 7, Jueves 9, Martes 14 y Jueves 16 de septiembre, de 18:30 a 21:30
Auditorio IEEE / CICOMRA
Avda. Córdoba 744, 1er. Piso 'B', Buenos Aires

Aranceles
Profesional socio* $160.- Profesional no socio: $ 200.-
Estudiante socios* $ 80.- Estudiante no socio $ 120.-
* Incluye socios de IEEE, AADECA, CICOMRA, CIENCIA HOY, COPITEC y SADIO.



IEEE Signal Processing Society- Capítulo Argentino
Curso SP03: “Aplicaciones con Procesadores Digitales de Señales"

Objetivo
Implementar aplicaciones en un DSP, desde el diseño teórico hasta la puesta en marcha del sistema. Los participantes podrán ser protagonistas y aplicar conceptos impartidos.

Dirigido a
Profesionales en el área de la ingeniería electrónica con formación básica en procesamiento digital de señales que deseen experiencia práctica.

Temario
1. Breve resumen de conceptos teóricos
2. Hardware de DSP
3. Software de DSP
4. Efectos digitales de audio
5. Implementación de Filtros Digitales (IIR y FIR)
6. Implementación de Transformada Rápida de Fourier

Conductores
Ing. Daniel Jacoby . Ingeniero Electrónico ITBA. Profesor Titular en el ITBA.
Ing. Roxana Saint-Nom . Ingeniera Electrónica ITBA. Profesora titular e investigadora en el ITBA

Fecha y lugar de realización
Martes 5, Jueves 7, Martes 12 y Jueves 14 de octubre, de 18:30 a 21:30
Auditorio IEEE / CICOMRA
Avda. Córdoba 744, 1er. Piso 'B', Buenos Aires

Aranceles
Profesional socio* $160.- Profesional no socio: $ 200.-
Estudiante socios* $ 80.- Estudiante no socio $ 120.-
* Incluye socios de IEEE, AADECA, CICOMRA, CIENCIA HOY, COPITEC y SADIO.



IEEE Computer Society - Capítulo Argentino
Programa de Conferencistas Distinguidos
Conferencias y Tutorial del Dr. Jaideep Srivastava

Dentro del marco del Programa de Conferencistas Distinguidos de la IEEE Computer Society , el Capitulo Argentino tiene el honor de anunciar la visita del Dr. Jaideep Srivastava a la Argentina. Durante la misma ofrecerá los días 20 y 22 de Septiembre dos Conferencias en Universidades locales y un Tutorial en ExpoComm, según se detalla más abajo.
El Dr. Srivastava también disertará el Viernes 24 por la mañana en Montevideo, en una actividad organizada por IEEE Uruguay.

Las presentaciones se realizarán en Inglés.

* Lunes 20, 18:30, Universidad CAECE (Buenos Aires)
Conferencia: Web Mining

* Miercoles 22, 10:30, Facultad de Ingenieria UBA (Buenos Aires)
Conferencia: Data Mining for Computer Security

* ExpoComm
Tutorial: Web Mining Accomplishments and Future Directions
Para inscripcion en este Tutorial: http://www.expocomm.com.ar

Dr. Jaideep Srivastava
Dr. Jaideep Srivastava is a professor on the faculty of the University of Minnesota. Between 1999 and 2001 he took a two-year leave, during which he spent time at Amazon.com and at Yodlee Inc. This wide-ranging industry experience has provided him with a unique perspective on the application of various computer science technologies in various kinds of Web-based services. As a researcher, educator, consultant, and invited speaker in the areas of data mining, databases, artificial intelligence, and multimedia for over 15 years, Dr. Srivastava continues his active collaboration with the technology industry, both for research and technology transfer. Dr. Srivastava has supervised 20 Ph.D. dissertations and 39 MS theses, and has authored/co-authored over 175 papers in journals and conferences. He has chaired/co-chaired a number of conferences, and is on the editorial board of many journals. An often-invited participant in technical and technology strategy forums, Dr. Srivastava has presented at a multitude of industry, academic and government meetings. He has been involved in the organization of a number of conferences, and serves on the editorial board of various journals. The US federal government has solicited his opinion on computer science research as an expert witness. He also served in an advisory role to the government of India on various software technologies. Dr. Srivastava received his B.Tech. in Computer Science from the Indian Institute of Technology - Kanpur , and M.S. and Ph.D. in Computer Science from the University of California - Berkeley . He has been elected an IEEE Fellow for his contributions to Computer Science research.

Conferencia: Web Mining
From its very beginning, the potential of extracting valuable knowledge from the Web has been quite evident. Web mining - i.e. the application of data mining techniques to extract knowledge from Web content, structure, and usage - is the collection of technologies to fulfill this potential. Interest in Web mining has grown rapidly in its short existence, both in the research and practitioner communities. A number of new concepts, e.g. PageRank, hubs & authorities, web communities, web interestingness measures, etc., and techniques to compute them have been developed. In addition, a wide variety of commercial enterprises regularly use Web mining in their daily operations, e.g. Amazon, Yahoo, Google, etc. This talk provides an overview of the accomplishments of the field - both in terms of technologies and applications - and outlines key future research directions.

Conferencia: Data Mining for Computer Security
Today computers control power, oil and gas delivery, communication systems, transportation networks, banking and financial services, and various other infrastructure services critical to the functioning of our society. However, as the cost of the information processing and Internet accessibility falls, more and more organizations are becoming vulnerable to a wide variety of cyber threats. According to a recent survey by CERT/CC (Computer Emergency Response Team/Coordination Center), the rate of cyber attacks has been more than doubling every year in recent times. It has become increasingly important to make our information systems, especially those used for critical functions in the military and commercial sectors, resistant to and tolerant of such attacks.
Intrusion detection, as a special form of cyber threat analysis, includes identifying a set of malicious actions that compromise the integrity, confidentiality, and availability of information resources. Traditional methods for intrusion detection are based on extensive knowledge of signatures of known attacks. The signature database has to be manually revised for each new type of intrusion that is discovered. A significant limitation of signature-based methods is that they cannot detect emerging cyber threats, since by their very nature these threats are launched using previously unknown attacks. These limitations have led to an increasing interest in intrusion detection techniques based upon data mining.
The tremendous increase of novel cyber attacks has made data mining based intrusion detection techniques extremely useful in their detection. These techniques generally fall into one of two categories; misuse detection and anomaly detection. However, both approaches attempt to detect cyber attacks that occur very infrequently, but their consequences may be quite dramatic and often in a negative sense. In misuse detection, each instance in a data set is labeled as ‘normal' or ‘attack/intrusion' and a learning algorithm is trained over the labeled data. However, standard data mining techniques are not applicable due to issues including (i) dealing with skewed class distribution (attacks/intrusions correspond to a class of interest that is much smaller, i.e. rarer, than the class representing normal behavior) and (ii) learning from data streams (attacks/intrusions very often represent sequence of events). Anomaly detection, on the other hand, builds models of normal behavior, and automatically detects new types of intrusions as deviations from normal usage.
This tutorial-style talk will provide an up-to-date introduction to the increasingly important field of the data mining in intrusion detection, as well as an overview of research directions in this field. It will cover the most representative research projects and directions in intrusion detection based on data mining. There is also an ongoing project at our center related to the data mining applications in network intrusion detection, and plan to cover some of these activities in the talk.

Acknowledgement:
This is joint work with Dr. Aleksander Lazarevic and Prof. Vipin Kumar, and other members of the MINDS (Minnesota Intrusion Detection System) group. Details of MINDS are available at http://www.cs.umn.edu/research/minds/.

Mas información...
http://www.cs.umn.edu/faculty/srivasta.html
http://www.computer.org/chapter/DVP/Srivastrava.htm

 


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recuerde visitar periodicamente la seccion 'Noticias y Actividades'
en nuestra pagina web http://www.ieee.org.ar



IEEE Argentina - Oficina Administrativa:
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(C1054AAT) Ciudad Autónoma de Buenos Aires - República Argentina
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Fax: +(54 11) 4325 9604
E-mail: sec.argentina@ieee.org
WWW: http://www.ieee.org.ar



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