Rol y habilidades del CIO. Tres casos de estudio en Colombia: Alpina, Banco de Bogotá, Grupo Aval

Con base en la revisión de la literatura realizada acerca de los roles directivos y del rol de uno en particular que es el CIO, y tomando como referencia la información suministrada por los directivos de tecnologías de Información de las organizaciones Alpina, Banco de Bogotá y Grupo AVAL, el trabajo de investigación hace una descripción del contenido del rol de CIO e identifica las habilidades requeridas para el ejercicio de este rol en dichas organizaciones. Se espera que los resultados del presente estudio generen un valioso aporte como retroalimentación para la academia y las empresas acerca de la formación de los futuros CIO.

La competència "El treball col·laboratiu": una oportunitat per a incorporar les TIC en la didàctica universitària. Descripció de l'experiència amb la plataforma ACME (UdG) = La competencia "El trabajo colaborativo": una oportunidad para incorporar las TIC en la didáctica universitaria. Descripción de la experiencia con la plataforma ACME (UdG)

L'article és una reflexió sobre els requisits de formació dels professionals que demana la societat del coneixement. Un dels objectius més importants que ha de tenir la universitat en la societat del coneixement és la formació de professionals competents que tinguin prou eines intel·lectuals per a enfrontar-se a la incertesa de la informació, a la consciència que aquesta té una data de caducitat a curt termini i a l'ansietat que això provoca. Però, a més, també han de ser capaços de definir i crear les eines de treball amb què donaran sentit i eficàcia a aquest coneixement mudable i mutant. Per això, l'espai europeu d'ensenyament superior prioritza la competència transversal del treball col·laboratiu amb l'objectiu de promoure un aprenentatge autònom, compromès i adaptat a les noves necessitats de l'empresa del segle xxi. En aquest context, es presenta l'entorn teòric que fonamenta el treball desenvolupat a la plataforma informàtica ACME, que uneix el treball col·laboratiu i l'aprenentatge semipresencial o blended learning. Així mateix, es descriuen amb detall alguns exemples de wikis, paradigma del treball col·laboratiu, fets en assignatures impartides per la Universitat de Girona en l'espai virtual ACME

Memory-based Embodied Cognition: a computational architecture

At its most fundamental, cognition as displayed by biological agents (such as humans) may be said to consist of the manipulation and utilisation of memory. Recent discussions in the field of cognitive robotics have emphasised the role of embodiment and the necessity of a value or motivation for autonomous behaviour. This work proposes a computational architecture – the Memory-Based Cognitive (MBC) architecture – based upon these considerations for the autonomous development of control of a simple mobile robot. This novel architecture will permit the exploration of theoretical issues in cognitive robotics and animal cognition. Furthermore, the biological inspiration of the architecture is anticipated to result in a mobile robot controller which displays adaptive behaviour in unknown environments.

Review of computer vision in intelligent environment design

This paper discusses and compares the use of vision based and non-vision based technologies in developing intelligent environments. By reviewing the related projects that use vision based techniques in intelligent environment design, the achieved functions, technical issues and drawbacks of those projects are discussed and summarized, and the potential solutions for future improvement are proposed, which leads to the prospective direction of my PhD research.

The use of computer-based learning tools for teaching and clinical purposes: Interactive computing strategy for Iraq

Medical universities and teaching hospitals in Iraq are facing a lack of professional staff due to the ongoing violence that forces them to flee the country. The professionals are now distributed outside the country which reduces the chances for the staff and students to be physically in one place to continue the teaching and limits the efficiency of the consultations in hospitals. A survey was done among students and professional staff in Iraq to find the problems in the learning and clinical systems and how Information and Communication Technology could improve it. The survey has shown that 86% of the participants use the Internet as a learning resource and 25% for clinical purposes while less than 11% of them uses it for collaboration between different institutions. A web-based collaborative tool is proposed to improve the teaching and clinical system. The tool helps the users to collaborate remotely to increase the quality of the learning system as well as it can be used for remote medical consultation in hospitals.

Improving computer interaction for older people - studying mouse clicks

Interactions using a standard computer mouse can be particularly difficult for novice and older adult users. Tasks that involve positioning the mouse over a target and double-clicking to initiate some action can be a real challenge for many users. Hence, this paper describes a study that investigates the double-click interactions of older and younger adults and presents data that can help inform the development of methods of assistance. Twelve older adults (mean age = 63.9 years) and 12 younger adults (mean age = 20.8 years) performed click and double-click target selections with a computer mouse. Initial results show that older users make approximately twice as many errors as younger users when attempting double-clicks. For both age groups, the largest proportion of errors was due to difficulties with keeping the cursor steady between button presses. Compared with younger adults, older adults experienced more difficulties with performing two button presses within a required time interval. Understanding these interactions better is a step towards improving accessibility, and may provide some suggestions for future directions of research in this area.

The role of sketches in supporting near-synchronous remote communication in computer supported collaborative design

This paper presents recent research into the functions and value of sketch outputs during computer supported collaborative design. Sketches made primarily exploiting whiteboard technology are shown to support subjects engaged in remote collaborative design, particularly when constructed in ‘nearsynchronous’ communication. The authors define near-synchronous communication and speculate that it is compatible with the reflective and iterative nature of design activity. There appears to be significant similarities between the making of sketches in near-synchronous remote collaborative design and those made on paper in more traditional face-to-face settings With the current increase in the use of computer supported collaborative working (CSCW) in undergraduate and postgraduate design education it is proposed that sketches and sketching can make important contributions to design learning in this context

Finding the smallest eigenvalue by the inverse Monte Carlo method with refinement

Finding the smallest eigenvalue of a given square matrix A of order n is computationally very intensive problem. The most popular method for this problem is the Inverse Power Method which uses LU-decomposition and forward and backward solving of the factored system at every iteration step. An alternative to this method is the Resolvent Monte Carlo method which uses representation of the resolvent matrix [I -qA](-m) as a series and then performs Monte Carlo iterations (random walks) on the elements of the matrix. This leads to great savings in computations, but the method has many restrictions and a very slow convergence. In this paper we propose a method that includes fast Monte Carlo procedure for finding the inverse matrix, refinement procedure to improve approximation of the inverse if necessary, and Monte Carlo power iterations to compute the smallest eigenvalue. We provide not only theoretical estimations about accuracy and convergence but also results from numerical tests performed on a number of test matrices.

State of the art of learning styles-based adaptive educational hypermedia systems (Ls-Baehss)

The notion that learning can be enhanced when a teaching approach matches a learner’s learning style has been widely accepted in classroom settings since the latter represents a predictor of student’s attitude and preferences. As such, the traditional approach of ‘one-size-fits-all’ as may be applied to teaching delivery in Educational Hypermedia Systems (EHSs) has to be changed with an approach that responds to users’ needs by exploiting their individual differences. However, establishing and implementing reliable approaches for matching the teaching delivery and modalities to learning styles still represents an innovation challenge which has to be tackled. In this paper, seventy six studies are objectively analysed for several goals. In order to reveal the value of integrating learning styles in EHSs, different perspectives in this context are discussed. Identifying the most effective learning style models as incorporated within AEHSs. Investigating the effectiveness of different approaches for modelling students’ individual learning traits is another goal of this study. Thus, the paper highlights a number of theoretical and technical issues of LS-BAEHSs to serve as a comprehensive guidance for researchers who interest in this area.

WCCC 2015: the 21st world computer chess championship

Nine chess programs competed in July 2015 in the ICGA's World Computer Chess Championship at the Computer Science department of Leiden University. This is the official report of the event.

Bayesian model comparison with un-normalised likelihoods

Models for which the likelihood function can be evaluated only up to a parameter-dependent unknown normalizing constant, such as Markov random field models, are used widely in computer science, statistical physics, spatial statistics, and network analysis. However, Bayesian analysis of these models using standard Monte Carlo methods is not possible due to the intractability of their likelihood functions. Several methods that permit exact, or close to exact, simulation from the posterior distribution have recently been developed. However, estimating the evidence and Bayes’ factors for these models remains challenging in general. This paper describes new random weight importance sampling and sequential Monte Carlo methods for estimating BFs that use simulation to circumvent the evaluation of the intractable likelihood, and compares them to existing methods. In some cases we observe an advantage in the use of biased weight estimates. An initial investigation into the theoretical and empirical properties of this class of methods is presented. Some support for the use of biased estimates is presented, but we advocate caution in the use of such estimates.

Efficiency issues of evolutionary k-means

One of the top ten most influential data mining algorithms, k-means, is known for being simple and scalable. However, it is sensitive to initialization of prototypes and requires that the number of clusters be specified in advance. This paper shows that evolutionary techniques conceived to guide the application of k-means can be more computationally efficient than systematic (i.e., repetitive) approaches that try to get around the above-mentioned drawbacks by repeatedly running the algorithm from different configurations for the number of clusters and initial positions of prototypes. To do so, a modified version of a (k-means based) fast evolutionary algorithm for clustering is employed. Theoretical complexity analyses for the systematic and evolutionary algorithms under interest are provided. Computational experiments and statistical analyses of the results are presented for artificial and text mining data sets. (C) 2010 Elsevier B.V. All rights reserved.

Towards improving cluster-based feature selection with a simplified silhouette filter

This paper proposes a filter-based algorithm for feature selection. The filter is based on the partitioning of the set of features into clusters. The number of clusters, and consequently the cardinality of the subset of selected features, is automatically estimated from data. The computational complexity of the proposed algorithm is also investigated. A variant of this filter that considers feature-class correlations is also proposed for classification problems. Empirical results involving ten datasets illustrate the performance of the developed algorithm, which in general has obtained competitive results in terms of classification accuracy when compared to state of the art algorithms that find clusters of features. We show that, if computational efficiency is an important issue, then the proposed filter May be preferred over their counterparts, thus becoming eligible to join a pool of feature selection algorithms to be used in practice. As an additional contribution of this work, a theoretical framework is used to formally analyze some properties of feature selection methods that rely on finding clusters of features. (C) 2011 Elsevier Inc. All rights reserved.