Visual Exploration of Health Information for Children

by Frans van der Sluis, Sergio Duarte Torres, Djoerd Hiemstra, Betsy van Dijk, Frea Kruisinga 

Children experience several difficulties retrieving informa- tion using current Information Retrieval (IR) systems. Particularly, chil- dren struggle to find the right keywords to construct queries given their lack of domain knowledge. This problem is even more critical in the case of the specialized health domain. In this work we present a novel method to address this problem using a cross-media search interface in which the textual data is searched through visual images. This solution aims to solve the recall and recognition problem which is salient for health information, by replacing the need for a vocabulary with the easy task of recognising the different body parts. Read the paper.

Workshop at COMMIT: Planning your international career

Workshop organized by Peter Apers and Iddo Bante. During this workshop we will share experience and instruments to facilitate the next step in your career at an international level. Talks will be given on Horizon 2020, ERC Grants, ICT Labs, working for international R&D labs. We will also address your requests for instruments for your next step.
Presentations by: Iddo Bante, managing director at the CTIT at University Twente and Sergio Duarte Torres

A Novel Image Encryption Scheme Based on a Generalized Chinese Remainder Theorem

by Sergio Duarte Torres, David Becerra Romero, Luis Niño and Yoan Pinzon.

In this paper, a novel method for image encryption based on a Generalized Chinese Remainder Theorem (GCRT) is presented. The proposed method is based on the work developed by Jagannathan et al. Some modifications are proposed in order to increase the method’s encryption quality and its robustness against attacks. Specifically, the inclusion of a vector to reduce the segment pixel space and a Generalized Chinese Remainder Theorem (GCRT) algorithm are proposed. These vectors are generated randomly which allows its use as private keys joining these unrestricted key values generated by the GCRT algorithm. An analysis to study a system where the RGB channels are independently encrypted is performed. Some experiments were carried out to validate the proposed model obtaining very promising results. Read the paper.

A Model for Resource Assignment to Transit Routes in Bogota Transportation System Transmilenio

by Sergio Duarte Torres, David Becerra Romero and Luis Niño.

In this work, a model based on genetic algorithms, queue theory and graph theory for route planning in a mass transportation system is presented. Most important features of the proposed approach are i) the modeling of the Americas line in the mass transportation system Transmilenio in Bogota; ii) Data preprocessing using graph theory to characterize the shortest routes between all the possible combinations of destination and source stations; iii) the optimization of travel time by route assignment using genetic algorithms iv) the simulation of events using the Poisson and Erlang distributions, corresponding to bus arrival at specific stations and to users waiting time. An experimental methodology was developed to validate the proposed approach. Read the paper (In Spanish).

A novel ab-initio genetic-based approach for protein folding prediction

by Sergio Duarte Torres, David Becerra, Luis Niño and Yoan Pinzon. 

In this paper, a model based on genetic algorithms for protein folding prediction is proposed. The most important features of the proposed approach are: i) Heuristic secondary structure information is used in the initialization of the genetic algorithm; ii) An enhanced 3D spatial representation called cube-octahedron is used, also, an expansion technique is proposed in order to reduce the computational complexity and spatial constraints; iii) Data preprocessing of geometric features to characterize the cube-octahedron using twelve basic vectors to define the nodes. Additionally, biological information (torsion angles, bond angles and secondary structure conformations) was pre-processed through an analysis of all possible combinations of the basic vectors which satisfy the biological constrains defined by the spatial representation; and iv) Hashing techniques were used to improve the computational efficiency. The pre-processed information was stored in hash tables, which are intensively used by the genetic algorithm. Some experiments were carried out to validate the proposed model obtaining very promising results. Read the paper.