• International Conference on Electronics, Communications and Computers

Keynote lectures « Conielecomp2013
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Keynote lectures


Optimal FIR versus Kalman Filtering for State Estimation and Signal Processing

PhD. Yuriy S. Shmaliy, IEEE Fellow

Universidad de Guanajuato, México

Abstract: Optimal estimation is often provided in state space with finite samples requiring finite impulse response (FIR) filtering, prediction and smoothing. Although the Kalman filter is a traditional tool in state space, its optimal implementation is commonly problematic due to unknown noise statistics and initial error statistics. In this talk, we show that FIR filtering circumvents this disadvantage in the iterative Kalman-like unbiased FIR (UFIR) estimation algorithm ignoring noise statistics and initial error statistics. The optimal UFIR (OUFIR) algorithm requires the optimal averaging interval that can easily be estimated experimentally. The UFIR algorithm demonstrates the bounded input/bounded output (BIBO) stability and has better robustness against uncertainties. It also has lower round-off errors and lower sensitivity to noise and initial conditions. We introduce the UFIR algorithm in detail for polynomials and harmonic signals with simple examples. We also show that errors in UFIR estimators are well bounded in the three-sigma sense via the noise power gain. Many applications are given for system state estimation, tracking of linear and nonlinear models, GPS-based timekeeping, denoising of medical signals, detection of biosignals, enhancement of ultrasound images, and voice pitch tracking.


Today students going towards tomorrow innovators using PTC-CREO Software

Eng. Eduardo Méndez Rivera

PTC, México

Abstract: PTC offers solutions for product development through: PTC Creo design software tools integrated 3D CAD / CAM / CAE integrated parametric, to design faster than ever, maximizing innovation and quality to create exceptional products, provides the broadest range of 3D CAD design capabilities, efficiency and flexibility to help you meet the most demanding design challenges, including adapting to changes in the final stages, work with data from multiple CAD systems and design electromechanical.


Adobe: Changing the education through digital experiences

Luis R. Caballero

ADOBE Systems Incorporated

Abstract: We as a society are in the midst of a transformation that affects not only individuals, but every organization trying to reach them. This is a much broader shift than just the move to mobile — it’s a shift to multiple screens, when people are interacting across many devices — personal computers, mobile phones, tablets, Internet televisions, car dashboards and countless other touch points. People want to connect with content from one screen to another screen in a continuous process, depending on where they are and what they’re doing. They want to look at magazines and books and television shows and play games. They want to connect with peers and share their ideas with other people. They want to publish their own content using whatever device they’re on. We will help the members of your campus community to create, deliver, and optimize compelling content across media and devices, we help you prepare students for success and run operations more efficiently in the digital age.


ETAP Software for Analysis and Design of Power Systems

M. Sc. David G. Romero-Gomez

Manager ETAP México

Abstract: ETAP is the most comprehensive analysis platform for the design, simulation, operation, and automation of generation, distribution, and industrial power systems. ETAP is developed under an established quality assurance program and is used worldwide as high impact software. Libraries are Verified and Validated (V&V) against field results, real system measurements, established programs, and hand calculations in order to ensure its technical accuracy. Each release of ETAP undergoes a complete V&V process using thousands of test cases for each and every calculation module and library data.

Unique to ETAP is the transformation from a flat database into a multi-dimensional one. This eliminates the need to make hundreds of copies of the database.

ETAP offers a suite of fully integrated Electrical solutions including arc flash, load flow, short circuit, transient stability, relay coordination, cable ampacity, optimal power flow, renewables and more. Software integrates updated international standards such as ANSI, IEC, IEEE, ICEA, NEC, NFPA, BS.

Its modular functionality can be customized to fit the needs of any company, from small to large power systems.

As a fully integrated enterprise solution, ETAP extends to a Real-Time Intelligent Power Management System to monitor, control, automate, simulate, and optimize the operation of power systems. Other important applications are Smart Grid and Transmission & Distribution solutions.

ETAP is used by engineers globally on several industries such as Consulting Firms, Data Centers & Mission Critical Facilities, Oil & Gas, Generation Plants, Nuclear Generation Plants, Transmission & Distribution, Government and Military Facilities, Metals & Mining, Manufacturing, Renewable Energy, Transportation, Universities.


Antennas design for wireless medical sensors

Mtro. Marco A. de Roman

Ingenieros Médicos, México

Abstract: World population grows increasingly, for the first time ever got to the point that the urban population is larger than the rural. This leads us to consider offering health services to more people living in cities, without neglecting those living in remote areas. Wireless sensors for medical application can be used for this proposal, since they can be carried on clothing, shoes, sunglasses and even can be implanted in the human body, because this kind of sensors are small, cheap and works with low energy consume. This technology, together with information technologies, represent a new health promise. However, these new devices have a problem with the antenna design, related with the efficienty to collect external power to feed the entire chip. we present some alternatives to solve this problem.


A document is known by the company it keeps: Neighborhood consensus for short text categorization

Dr. Manuel Montes y Gómez


Abstract: During the last decades the Web has become the greatest repository of digital information. In order to organize all this information, several text categorization methods have been developed, achieving accurate results in most cases and in very different domains. Due to the recent usage of Internet as communication media, short texts such as news, tweets, blogs, and product reviews are more common every day. In this context, there are two main challenges; on the one hand, the length of these documents is short, and therefore, the word frequencies are not informative enough, making text categorization even more difficult than usual. On the other hand, topics are changing constantly at a fast rate, causing the lack of adequate amounts of training data. In order to deal with these two problems we consider a text classification method that is supported on the idea that similar documents may belong to the same category. Mainly, we propose a neighborhood consensus classification method that classifies documents by considering their own.


Addressing data management on the cloud : tackling the big data challenges

PhD. Genoveva Vargas-Solar

CNRS, France

Abstract:The increasing adoption of the cloud computing paradigm has motivated a redefinition of traditional software development methods. In particular, data storage management has received a great deal of attention, due to a growing interest in the challenges and opportunities associated to the NoSQL movement. However, appropriate selection, administration and use of cloud storage implementations remain a highly technical endeavor, due to large differences in the way data is represented, stored and accessed by these systems. This presentation proposes solutions for promoting polyglot persistence for building cloud aware database applications by making dependencies between high-level data models and cloud storage implementations transparent. In this way, developers depend only on high-level data models, and then rely on transformation procedures to deal with particular cloud storage details, such as different APIs and deployment providers, and are able to target multiple cloud storage environments, without modifying their core data models.

Information as well as information about the category assigned to other similar documents from the same target collection. Experimental results indicate that leveraging information from similar documents helped to improve classification accuracy and that the proposed method is especially useful when labeled training resources are limited.