Research-action Methodology between Computer Science and Educational Psychology: a Multidisciplinary Approach

Computer science studies possess a strong multidisciplinary aptitude since most graduates do their professional work outside of a computing environment, in close collaboration with professionals from many different areas. However, the training offered in computer science studies lacks that multidisciplinary factor, focusing more on purely technical aspects. In this paper we present a novel experience where computer studies and educational psychology find a common ground and realistic working through laboratory practices. Specifically, the work enables students of computer science education the development of diagnosis support systems, with artificial intelligence techniques, which could then be used for future educational psychologists. The applications developed by computer science students are the creation of a model for the diagnosis of pervasive developmental disorders (PDD), sometimes also commonly called the autism spectrum disorders (ASD). The complexity of this diagnosis, not only by the exclusive characteristics of every person who suffers from it, but also by the large numbers of variables involved in it, requires very strong and close interdisciplinary participation. This work demonstrates that it is possible to intervene in a curricular perspective, in the university, to promote the development of interpersonal skills. What can be shown, in this way, is a methodology for interdisciplinary practices design and a guide for monitoring and evaluation. The results are very encouraging since we obtained significant differences in academic achievement between students who attended a course using the new methodology and those who did not use it.

Spanish Nursing Students' Practical Experience of Computer Applications in Nursing

This study aimed to determine the level of computer practical experience in a sample of Spanish nursing students. Each student was given a Spanish language questionnaire, modified from an original used previously with medical students at the Medical School of North Carolina University (USA) and also at the Education Unit of Hospital General Universitario del Mar (Spain). The 10-item self-report questionnaire probed for information about practical experience with computers. A total of 126 students made up the sample. The majority were female (80.2%; n=101). The results showed that just over half (57.1%, n=72) of the students had used a computer game (three or more times before), and that only one third (37.3%, n=47) had the experience of using a word processing package. Moreover, other applications and IT-based facilities (e.g. statistical packages, e-mail, databases, CD-ROM searches, programming languages and computer-assisted learning) had never been used by the majority of students. The student nurses' practical experience was less than that reported for medical students in previous studies.

Comparative analysis of constructive solutions for thermal insulation by using computer applications in building rehabilitation in Mediterranean climate. The Spanish case

The new Spanish legislation in Energy Saving, similar to European regulation, provides new technical requirements to adequate technical solutions used in integral rehabilitation of existing buildings. The aim of this paper is to present, analyze and discuss the main thermal insulation constructive solutions best suited to a Mediterranean climate, and conclude on their suitability under the legislation in Energy Saving. The proposed methodology is based on the most usual constructive solutions in integral rehabilitation of buildings by analyzing their outstanding design features, by studying its construction details and then by applying the software provided by the Spanish legislation of energy efficiency in buildings. The results of the study evaluate and classify several solutions for façade rehabilitation according to energy efficiency criteria and their suitability for this type of weather, verifying the necessity of using software applications in energy saving for the proper design of constructive solutions in building rehabilitation.

Open educational resources: the role of OCW, blogs and videos in computer network classrooms

This paper analyzes the learning experiences and opinions obtained from a group of undergraduate students in their interaction with several on-line multimedia resources included in a free on-line course about Computer Networks. These new educational resources employed are based on the Web 2.0 approach such as blogs, videos and virtual labs which have been added in a web-site for distance self-learning.

Developing Semantic Rich Internet Applications with the Sm4RIA Extension for OIDE

This paper introduces the Sm4RIA Extension for OIDE, which implements the Sm4RIA approach in OIDE (OOH4RIA Integrated Development Environment). The application, based on the Eclipse framework, supports the design of the Sm4RIA models as well as the model-to-model and model-to-text transformation processes that facilitate the generation of Semantic Rich Internet Applications, i.e., RIA applications capable of sharing data as Linked data and consuming external data from other sources in the same manner. Moreover, the application implements mechanisms for the creation of RIA interfaces from ontologies and the automatic generation of administration interfaces for a previously design application.

Web-based OERs in Computer Networks

Learning and teaching processes are continually changing. Therefore, design of learning technologies has gained interest in educators and educational institutions from secondary school to higher education. This paper describes the successfully use in education of social learning technologies and virtual laboratories designed by the authors, as well as videos developed by the students. These tools, combined with other open educational resources based on a blended-learning methodology, have been employed to teach the subject of Computer Networks. We have verified not only that the application of OERs into the learning process leads to a significantly improvement of the assessments, but also that the combination of several OERs enhances their effectiveness. These results are supported by, firstly, a study of both students’ opinion and students’ behaviour over five academic years, and, secondly, a correlation analysis between the use of OERs and the grades obtained by students.

Evaluation of complex temporal questions in CLEF-QA

This paper presents the evaluation of a QA system for the treatment of complex temporal questions. The system was implemented in a multilayered architecture where complex temporal questions are first decomposed into simple questions, according to the temporal relations expressed in the original question. These simple questions are then processed independently by our standard Question Answering engine and their respective answers are filtered to satisfy the temporal restrictions of each simple question. The answers to the simple decomposed questions are then combined, according to the temporal relations extracted from the original complex question, to give the final answer. This evaluation was performed as a pilot task in the Spanish QA Track of the Cross Language Evaluation Forum 2004.

Evaluating EmotiBlog robustness for sentiment analysis tasks

EmotiBlog is a corpus labelled with the homonymous annotation schema designed for detecting subjectivity in the new textual genres. Preliminary research demonstrated its relevance as a Machine Learning resource to detect opinionated data. In this paper we compare EmotiBlog with the JRC corpus in order to check the EmotiBlog robustness of annotation. For this research we concentrate on its coarse-grained labels. We carry out a deep ML experimentation also with the inclusion of lexical resources. The results obtained show a similarity with the ones obtained with the JRC demonstrating the EmotiBlog validity as a resource for the SA task.

Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.

A combined probabilistic framework for learning gestures and actions

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.

Extractive text summarization: can we use the same techniques for any text?

In this paper we address two issues. The first one analyzes whether the performance of a text summarization method depends on the topic of a document. The second one is concerned with how certain linguistic properties of a text may affect the performance of a number of automatic text summarization methods. For this we consider semantic analysis methods, such as textual entailment and anaphora resolution, and we study how they are related to proper noun, pronoun and noun ratios calculated over original documents that are grouped into related topics. Given the obtained results, we can conclude that although our first hypothesis is not supported, since it has been found no evident relationship between the topic of a document and the performance of the methods employed, adapting summarization systems to the linguistic properties of input documents benefits the process of summarization.

Towards a new proposal to evaluate the learning objects quality in learning strategies for education (QEES)

In Computer Science world several proposals have been developed for the assessment of the quality of the digital objects, based on the capabilities and facilities offered by current technologies and the available resources. Years ago researchers and specialists from both educational and technological areas have been committed to the development of strategies that improve the quality of education. At present, in the field of teaching-learning, another important aspect is the need to improve the manner of gaining knowledge and learning in education, which the use of learning strategies is a major advance in the teaching-learning process in institutions of higher education. This paper presents QEES, a proposal for evaluating the quality of the learning objects employed on learning strategies to support students during their education processes by using information extraction techniques and ontologies.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

Experiences Using an Open Source Sofware Library to Teach Computer Vision Subjects

Machine vision is an important subject in computer science and engineering degrees. For laboratory experimentation, it is desirable to have a complete and easy-to-use tool. In this work we present a Java library, oriented to teaching computer vision. We have designed and built the library from the scratch with enfasis on readability and understanding rather than on efficiency. However, the library can also be used for research purposes. JavaVis is an open source Java library, oriented to the teaching of Computer Vision. It consists of a framework with several features that meet its demands. It has been designed to be easy to use: the user does not have to deal with internal structures or graphical interface, and should the student need to add a new algorithm it can be done simply enough. Once we sketch the library, we focus on the experience the student gets using this library in several computer vision courses. Our main goal is to find out whether the students understand what they are doing, that is, find out how much the library helps the student in grasping the basic concepts of computer vision. In the last four years we have conducted surveys to assess how much the students have improved their skills by using this library.

An Electronic Reconfigurable Neural Architecture for Intrusion Detection

The explosive growth of the traffic in computer systems has made it clear that traditional control techniques are not adequate to provide the system users fast access to network resources and prevent unfair uses. In this paper, we present a reconfigurable digital hardware implementation of a specific neural model for intrusion detection. It uses a specific vector of characterization of the network packages (intrusion vector) which is starting from information obtained during the access intent. This vector will be treated by the system. Our approach is adaptative and to detecting these intrusions by using a complex artificial intelligence method known as multilayer perceptron. The implementation have been developed and tested into a reconfigurable hardware (FPGA) for embedded systems. Finally, the Intrusion detection system was tested in a real-world simulation to gauge its effectiveness and real-time response.