EPA-0882 - Prediction of diagnosis of early-onset schizophrenia spectrum disorders using support vector machines

To develop a Support Vector Machine (SVM) algorithm as a predictive tool for diagnostic outcome in patients with FE-EOP, based on clinical and biomedical data at the emergence of the illness.

The usefulness of Usability and User Experience evaluation methods on an e-Learning platform development from a developer's perspective: A case study

The development of a web platform is a complex and interdisciplinary task, where people with different roles such as project manager, designer or developer participate. Different usability and User Experience evaluation methods can be used in each stage of the development life cycle, but not all of them have the same influence in the software development and in the final product or system. This article presents the study of the impact of these methods applied in the context of an e-Learning platform development. The results show that the impact has been strong from a developer's perspective. Developer team members considered that usability and User Experience evaluation allowed them mainly to identify design mistakes, improve the platform's usability and understand the end users and their needs in a better way. Interviews with potential users, clickmaps and scrollmaps were rated as the most useful methods. Finally, these methods were considered unanimously very useful in the context of the entire software development, only comparable to SCRUM meetings and overcoming the rest of involved factors.

A user-focused integrated system for sustainable refurbishment.

Nowadays, it is urgent to renovate a great number of residential buildings. The necessity of improving energy efficiency must also be considered as an opportunity to improve indoor comfort. To achieve this goal, it is essential to develop tools to be used in the decision-making process, aiming to refurbish buildings in an integrated, efficient and sustainable way. The integrated system developed is based on a set of indicators. Sustainability indicators are useful to synthesize and organize complex information. They can provide data to evaluate a process in different stages: evaluation, diagnosis, comparison and tracing. The set of proposed indicators aims to accomplish the holistic approach pursued by sustainable development. So, these indicators are divided into three groups: environmental, social and economic. However, the main innovation of the system of indicators is the social ones. The sustainable refurbishment system aims to be a user-focused one. Therefore, the starting point is the needs of the user and social indicators are developed around this. The system tackles the sustainable refurbishment of buildings beyond energy problems. It proposes incorporating users in the decision-making process involving them in the refurbishment and so, contributing to the success of the renovation. In order to achieve this target, three social indicators are used, divided into 10 sub-indicators, and a ?Questionnaire about Sustainable Refurbishment? is drawn up. This research has been carried out in the framework of ?Sustainable Refurbishment? Research and Development Project, an integrated project under the supervision of the Centro para el Desarrollo Tecnológico e Industrial (CDTI) from the Spanish Government, in which University and the Construction Industry collaborate. This research project aims to develop an integrated system for the retrofitting of existing buildings to improve their energy efficiency. Accordingly, an additional objective of the project is to improve quality of life of residents.

A supervised cooperative learning system for early detection of language disorders

The Quality of Life of a person may depend on early attention to his neurodevel-opment disorders in childhood. Identification of language disorders under the age of six years old can speed up required diagnosis and/or treatment processes. This paper details the enhancement of a Clinical Decision Support System (CDSS) aimed to assist pediatricians and language therapists at early identification and re-ferral of language disorders. The system helps to fine tune the Knowledge Base of Language Delays (KBLD) that was already developed and validated in clinical routine with 146 children. Medical experts supported the construction of Gades CDSS by getting scientific consensus from literature and fifteen years of regis-tered use cases of children with language disorders. The current research focuses on an innovative cooperative model that allows the evolution of the KBLD of Gades through the supervised evaluation of the CDSS learnings with experts¿ feedback. The deployment of the resulting system is being assessed under a mul-tidisciplinary team of seven experts from the fields of speech therapist, neonatol-ogy, pediatrics, and neurology.

Self-learning of fault diagnosis identification

A good and early fault detection and isolation system along with efficient alarm management and fine sensor validation systems are very important in today¿s complex process plants, specially in terms of safety enhancement and costs reduction. This paper presents a methodology for fault characterization. This is a self-learning approach developed in two phases. An initial, learning phase, where the simulation of process units, without and with different faults, will let the system (in an automated way) to detect the key variables that characterize the faults. This will be used in a second (on line) phase, where these key variables will be monitored in order to diagnose possible faults. Using this scheme the faults will be diagnosed and isolated in an early stage where the fault still has not turned into a failure.

Distributed Fault Diagnosis Using Bayesian Reasoning in MAGNETO

Many of the emerging telecom services make use of Outer Edge Networks, in particular Home Area Networks. The configuration and maintenance of such services may not be under full control of the telecom operator which still needs to guarantee the service quality experienced by the consumer. Diagnosing service faults in these scenarios becomes especially difficult since there may be not full visibility between different domains. This paper describes the fault diagnosis solution developed in the MAGNETO project, based on the application of Bayesian Inference to deal with the uncertainty. It also takes advantage of a distributed framework to deploy diagnosis components in the different domains and network elements involved, spanning both the telecom operator and the Outer Edge networks. In addition, MAGNETO features self-learning capabilities to automatically improve diagnosis knowledge over time and a partition mechanism that allows breaking down the overall diagnosis knowledge into smaller subsets. The MAGNETO solution has been prototyped and adapted to a particular outer edge scenario, and has been further validated on a real testbed. Evaluation of the results shows the potential of our approach to deal with fault management of outer edge networks.

Quality in Blended Learning in Higher Education. A proposal for an Evaluation Model.

This paper presents an analysis of different models used to assess the quality of formative actions, considering classroom learning and distance education courses. Taking as starting point one of the analyzed models, the paper sets out the necessity of developing a new model that could measure the quality of a blended formation process, by selecting the applicable indicators and proposing some new. The model is composed of seven different categories, which include a sum of thirty five indicators. They will be used to represent courses quality level in Kiviat?s diagrams. This model is currently being put into practice in a real university environment.

Self Learning and self evaluation exercises database in basic mechanics: a theoretical-practical approach

In the School of Mines of the Technical University of Madrid (UPM) the first course of different degrees has been implemented and adapted to the European Higher Educational Area (EHEA). In all of the degrees there is a first semester course which gathers all the contents of basic mechanics: from the first kinematics concepts to the rigid solid plane motion Before the Bologna process took place, the authors had established the final assessment of the theoretical contents through open questions of theoretical-practical character In the present work, the elaboration of a wide database containing theoretical-practical questions that students can access on line is presented. The questions are divided in thirteen different questionnaires composed of a number of questions randomly chosen from a certain group in the database. Each group corresponds to a certain learning objective that the student knows. After answering the questionnaire and checking the grade assigned according to the performance of the student, the pupils can see the correct response displayed on the screen and widely explained by the professors. This represents a 10% of the final grade. As the student can access the questionnaires as many times as they want, the main goal is the self-assessment of each learning objective and therefore, getting the students involved in their own learning process so they can decide how much time they need to acquire the required level.

A machine learning approach to identify clinical trials involving nanodrugs and nanodevices from ClinicalTrials.gov

BACKGROUND: Clinical Trials (CTs) are essential for bridging the gap between experimental research on new drugs and their clinical application. Just like CTs for traditional drugs and biologics have helped accelerate the translation of biomedical findings into medical practice, CTs for nanodrugs and nanodevices could advance novel nanomaterials as agents for diagnosis and therapy. Although there is publicly available information about nanomedicine-related CTs, the online archiving of this information is carried out without adhering to criteria that discriminate between studies involving nanomaterials or nanotechnology-based processes (nano), and CTs that do not involve nanotechnology (non-nano). Finding out whether nanodrugs and nanodevices were involved in a study from CT summaries alone is a challenging task. At the time of writing, CTs archived in the well-known online registry ClinicalTrials.gov are not easily told apart as to whether they are nano or non-nano CTs-even when performed by domain experts, due to the lack of both a common definition for nanotechnology and of standards for reporting nanomedical experiments and results. METHODS: We propose a supervised learning approach for classifying CT summaries from ClinicalTrials.gov according to whether they fall into the nano or the non-nano categories. Our method involves several stages: i) extraction and manual annotation of CTs as nano vs. non-nano, ii) pre-processing and automatic classification, and iii) performance evaluation using several state-of-the-art classifiers under different transformations of the original dataset. RESULTS AND CONCLUSIONS: The performance of the best automated classifier closely matches that of experts (AUC over 0.95), suggesting that it is feasible to automatically detect the presence of nanotechnology products in CT summaries with a high degree of accuracy. This can significantly speed up the process of finding whether reports on ClinicalTrials.gov might be relevant to a particular nanoparticle or nanodevice, which is essential to discover any precedents for nanotoxicity events or advantages for targeted drug therapy.

A holistic experience in the integrated learning of specialized English and content in Engineering degrees

This paper aims to outline a theory-based Content and Language Integrated Learning course and to establish the rationale for adopting a holistic approach to the teaching of languages in tertiary education. Our work focuses on the interdependence between Content and Language Integrated Learning (CLIL), and the use of Information and Communication Technologies (ICT), in particular regarding the learning of English within the framework of Telecommunications Engineering. The study first analyses the diverse components of the instructional approach and the extent to which this approach interrelates with technologies within the context of what we have defined as a holistic experience, since it also aims to develop a set of generic competences or transferable skills. Second, an example of a course project framed in this holistic approach is described in order to exemplify the specific actions suggested for learner autonomy and CLIL. The approach provides both an adequate framework as well as the conditions needed to carry out a lifelong learning experience within our context, a Spanish School of Engineering. In addition to specialized language and content, the approach integrates the learning of skills and capacities required by the new plans that have been established following the Bologna Declaration in 1999.

Metaphor and Genre: An Approach to improve the learning process of English for Aeronautics

This study suggests a theoretical framework for improving the teaching/ learning process of English employed in the Aeronautical discourse that brings together cognitive learning strategies, Genre Analysis and the Contemporary theory of Metaphor (Lakoff and Johnson 1980; Lakoff 1993). It maintains that cognitive strategies such as imagery, deduction, inference and grouping can be enhanced by means of metaphor and genre awareness in the context of content based approach to language learning. A list of image metaphors and conceptual metaphors which comes from the terminological database METACITEC is provided. The metaphorical terms from the area of Aeronautics have been taken from specialised dictionaries and have been categorised according to the conceptual metaphors they respond to, by establishing the source domains and the target domains, as well as the semantic networks found. This information makes reference to the internal mappings underlying the discourse of aeronautics reflected in five aviation accident case studies which are related to accident reports from the National Transportation Safety Board (NTSB) and provides an important source for designing language teaching tasks. La Lingüística Cognitiva y el Análisis del Género han contribuido a la mejora de la enseñanza de segundas lenguas y, en particular, al desarrollo de la competencia lingüística de los alumnos de inglés para fines específicos. Este trabajo pretende perfeccionar los procesos de enseñanza y el aprendizaje del lenguaje empleado en el discurso aeronáutico por medio de la práctica de estrategias cognitivas y prestando atención a la Teoría del análisis del género y a la Teoría contemporánea de la metáfora (Lakoff y Johnson 1980; Lakoff 1993). Con el propósito de crear recursos didácticos en los que se apliquen estrategias metafóricas, se ha elaborado un listado de metáforas de imagen y de metáforas conceptuales proveniente de la base de datos terminológica META-CITEC. Estos términos se han clasificado de acuerdo con las metáforas conceptuales y de imagen existentes en esta área de conocimiento. Para la enseñanza de este lenguaje de especialidad, se proponen las correspondencias y las proyecciones entre el dominio origen y el dominio meta que se han hallado en los informes de accidentes aéreos tomados de la Junta federal de la Seguridad en el Transporte (NTSB)

Evaluating a web-based clinical decision support system for language disorders screening in a nursery school

Background: Early and effective identification of developmental disorders during childhood remains a critical task for the international community. The second highest prevalence of common developmental disorders in children are language delays, which are frequently the first symptoms of a possible disorder. Objective: This paper evaluates a Web-based Clinical Decision Support System (CDSS) whose aim is to enhance the screening of language disorders at a nursery school. The common lack of early diagnosis of language disorders led us to deploy an easy-to-use CDSS in order to evaluate its accuracy in early detection of language pathologies. This CDSS can be used by pediatricians to support the screening of language disorders in primary care. Methods: This paper details the evaluation results of the ?Gades? CDSS at a nursery school with 146 children, 12 educators, and 1 language therapist. The methodology embraces two consecutive phases. The first stage involves the observation of each child?s language abilities, carried out by the educators, to facilitate the evaluation of language acquisition level performed by a language therapist. Next, the same language therapist evaluates the reliability of the observed results. Results: The Gades CDSS was integrated to provide the language therapist with the required clinical information. The validation process showed a global 83.6% (122/146) success rate in language evaluation and a 7% (7/94) rate of non-accepted system decisions within the range of children from 0 to 3 years old. The system helped language therapists to identify new children with potential disorders who required further evaluation. This process will revalidate the CDSS output and allow the enhancement of early detection of language disorders in children. The system does need minor refinement, since the therapists disagreed with some questions from the CDSS knowledge base (KB) and suggested adding a few questions about speech production and pragmatic abilities. The refinement of the KB will address these issues and include the requested improvements, with the support of the experts who took part in the original KB development. Conclusions: This research demonstrated the benefit of a Web-based CDSS to monitor children?s neurodevelopment via the early detection of language delays at a nursery school. Current next steps focus on the design of a model that includes pseudo auto-learning capacity, supervised by experts.

A flexible open source web platform to facilitate Learning Object evaluation

Systematic evaluation of Learning Objects is essential to make high quality Web-based education possible. For this reason, several educational repositories and e-Learning systems have developed their own evaluation models and tools. However, the differences of the context in which Learning Objects are produced and consumed suggest that no single evaluation model is sufficient for all scenarios. Besides, no much effort has been put in developing open tools to facilitate Learning Object evaluation and use the quality information for the benefit of end users. This paper presents LOEP, an open source web platform that aims to facilitate Learning Object evaluation in different scenarios and educational settings by supporting and integrating several evaluation models and quality metrics. The work exposed in this paper shows that LOEP is capable of providing Learning Object evaluation to e-Learning systems in an open, low cost, reliable and effective way. Possible scenarios where LOEP could be used to implement quality control policies and to enhance search engines are also described. Finally, we report the results of a survey conducted among reviewers that used LOEP, showing that they perceived LOEP as a powerful and easy to use tool for evaluating Learning Objects.

Towards a Learning Object pedagogical quality metric based on the LORI evaluation model

Evaluating and measuring the pedagogical quality of Learning Objects is essential for achieving a successful web-based education. On one hand, teachers need some assurance of quality of the teaching resources before making them part of the curriculum. On the other hand, Learning Object Repositories need to include quality information into the ranking metrics used by the search engines in order to save users time when searching. For these reasons, several models such as LORI (Learning Object Review Instrument) have been proposed to evaluate Learning Object quality from a pedagogical perspective. However, no much effort has been put in defining and evaluating quality metrics based on those models. This paper proposes and evaluates a set of pedagogical quality metrics based on LORI. The work exposed in this paper shows that these metrics can be effectively and reliably used to provide quality-based sorting of search results. Besides, it strongly evidences that the evaluation of Learning Objects from a pedagogical perspective can notably enhance Learning Object search if suitable evaluations models and quality metrics are used. An evaluation of the LORI model is also described. Finally, all the presented metrics are compared and a discussion on their weaknesses and strengths is provided.

Ontology Evaluation: a pitfall-based approach to ontology diagnosis

La evaluación de ontologías, incluyendo diagnóstico y reparación de las mismas, es una compleja actividad que debe llevarse a cabo en cualquier proyecto de desarrollo ontológico para comprobar la calidad técnica de las ontologías. Sin embargo, existe una gran brecha entre los enfoques metodológicos sobre la evaluación de ontologías y las herramientas que le dan soporte. En particular, no existen enfoques que proporcionen guías concretas sobre cómo diagnosticar y, en consecuencia, reparar ontologías. Esta tesis pretende avanzar en el área de la evaluación de ontologías, concretamente en la actividad de diagnóstico. Los principales objetivos de esta tesis son (a) ayudar a los desarrolladores en el diagnóstico de ontologías para encontrar errores comunes y (b) facilitar dicho diagnóstico reduciendo el esfuerzo empleado proporcionando el soporte tecnológico adecuado. Esta tesis presenta las siguientes contribuciones: • Catálogo de 41 errores comunes que los ingenieros ontológicos pueden cometer durante el desarrollo de ontologías. • Modelo de calidad para el diagnóstico de ontologías alineando el catálogo de errores comunes con modelos de calidad existentes. • Diseño e implementación de 48 métodos para detectar 33 de los 41 errores comunes en el catálogo. • Soporte tecnológico OOPS!, que permite el diagnstico de ontologías de forma (semi)automática. De acuerdo con los comentarios recibidos y los resultados de los test de satisfacción realizados, se puede afirmar que el enfoque desarrollado y presentado en esta tesis ayuda de forma efectiva a los usuarios a mejorar la calidad de sus ontologías. OOPS! ha sido ampliamente aceptado por un gran número de usuarios de formal global y ha sido utilizado alrededor de 3000 veces desde 60 países diferentes. OOPS! se ha integrado en software desarrollado por terceros y ha sido instalado en empresas para ser utilizado tanto durante el desarrollo de ontologías como en actividades de formación. Abstract Ontology evaluation, which includes ontology diagnosis and repair, is a complex activity that should be carried out in every ontology development project, because it checks for the technical quality of the ontology. However, there is an important gap between the methodological work about ontology evaluation and the tools that support such an activity. More precisely, not many approaches provide clear guidance about how to diagnose ontologies and how to repair them accordingly. This thesis aims to advance the current state of the art of ontology evaluation, specifically in the ontology diagnosis activity. The main goals of this thesis are (a) to help ontology engineers to diagnose their ontologies in order to find common pitfalls and (b) to lessen the effort required from them by providing the suitable technological support. This thesis presents the following main contributions: • A catalogue that describes 41 pitfalls that ontology developers might include in their ontologies. • A quality model for ontology diagnose that aligns the pitfall catalogue to existing quality models for semantic technologies. • The design and implementation of 48 methods for detecting 33 out of the 41 pitfalls defined in the catalogue. • A system called OOPS! (OntOlogy Pitfall Scanner!) that allows ontology engineers to (semi)automatically diagnose their ontologies. According to the feedback gathered and satisfaction tests carried out, the approach developed and presented in this thesis effectively helps users to increase the quality of their ontologies. At the time of writing this thesis, OOPS! has been broadly accepted by a high number of users worldwide and has been used around 3000 times from 60 different countries. OOPS! is integrated with third-party software and is locally installed in private enterprises being used both for ontology development activities and training courses.