Educating in Project Management: an innovative approach. A shared-experience among Spanish Universities

This work presents an educational formal initiative aimed to monitor the acquisition and strengthening of competences by students that are being taught in project management subject. Groups of students belonging to three universities, embracing different knowledge areas such as engineering, biology, etc., were selected to run the experience. All of them had nevertheless a common and basic starting point: inexperience in project management field. In this scenario, we propose a new theoretical and practical approach oriented to reinforce problem-solving and related competences in a project management subject context. For this purpose, a Project-Based Learning (PjBL) initiative has been specifically designed and developed. The main idea is to bring a real world engineering project management case into the classroom, where students must face up to a completely new learning approach –groups in different locations, collaborative mode and unspecific solution, supported by a powerful internet platform:.project.net (http://www.Project.net). Other relevant aspects such as project climate, knowledge increasing, have also been monitored during the course. Results show and overall improvement in key competences. The obtained information will be used in two ways: to feed the students back about personal opportunities for improvement in specific competences, and to fine-tune the experience for further initiatives.

Knowledge Management and Information Systems based on Workflow Technology

Knowledge management is critical for the success of virtual communities, especially in the case of distributed working groups. A representative example of this scenario is the distributed software development, where it is necessary an optimal coordination to avoid common problems such as duplicated work. In this paper the feasibility of using the workflow technology as a knowledge management system is discussed, and a practical use case is presented. This use case is an information system that has been deployed within a banking environment. It combines common workflow technology with a new conception of the interaction among participants through the extension of existing definition languages.

Project-based learning experience on Data Structures course

This paper presents the innovations in the practical work of the Data Structures subject carried out in the last five years, including a transition period and a first year of implantation of the European Higher Education Area. The practical coursework is inspired by a project-based methodology and from 2008/2009 additional laboratory sessions are included in the subject schedule. We will present the academic results and ratios of the mentioned time period which imply a significant improvement on students' performance.

Knowledge pipeline in freight pipeline industry: competence- based model for open innovation

There is growing concern over the challenges for innovation in Freight Pipeline industry. Since the early works of Chesbrough a decade ago, we have learned a lot about the content, context and process of open innovation. However, much more research is needed in Freight Pipeline Industry. The reality is that few corporations have institutionalized open innovation practices in ways that have enabled substantial growth or industry leadership. Based on this, we pursue the following question: How does a firm’s integration into knowledge networks depend on its ability to manage knowledge? A competence-based model for freight pipeline organizations is analysed, this model should be understood by any organization in order to be successful in motivating professionals who carry out innovations and play a main role in collaborative knowledge creation processes. This paper aims to explain how can open innovation achieve its potential in most Freight Pipeline Industries.

A knowledge-based method for generating summaries of spatial movement in geographic areas

In this article we describe a method for automatically generating text summaries of data corresponding to traces of spatial movement in geographical areas. The method can help humans to understand large data streams, such as the amounts of GPS data recorded by a variety of sensors in mobile phones, cars, etc. We describe the knowledge representations we designed for our method and the main components of our method for generating the summaries: a discourse planner, an abstraction module and a text generator. We also present evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

A knowledge based framework to support active aging at home based environments

Information and Communication Technologies can support Active Aging strategies in a scenario like the Smart Home. This paper details a person centered distributed framework, called TALISMAN+, whose aim is to promote personal autonomy by taking advantage of knowledge based technologies, sensors networks, mobile devices and internet. The proposed solution can support an elderly person to keep living alone at his house without being obliged to move to a residential center. The framework is composed by five subsystems: a reasoning module that is able to take local decisions at home in order to support active aging, a biomedical variables telemonitorisation platform running on a mobile device, a hybrid reasoning middleware aimed to assess cardiovascular risk in a remote way, a private vision based sensor subsystem, and a secure telematics solution that guarantees confidentiality for personal information. TALISMAN+ framework deployment is being evaluated at a real environment like the Accessible Digital Home.

Preliminary approach to neutron instrument selecction at ESSB-Bilbao based on experience at ISIS molecular spectroscopy group

Collaborative efforts between the Neutronics and Target Design Group at the Instituto de Fusión Nuclear and the Molecular Spectroscopy Group at the ISIS Pulsed Neutron and Muon Source date back to 2012 in the context of the ESS-Bilbao project. The rationale for these joint activities was twofold, namely: to assess the realm of applicability of the low-energy neutron source proposed by ESS-Bilbao - for details; and to explore instrument capabilities for pulsed-neutron techniques in the range 0.05-3 ms, a time range where ESS-Bilbao and ISIS could offer a significant degree of synergy and complementarity. As part of this collaboration, J.P. de Vicente has spent a three-month period within the ISIS Molecular Spectroscopy Group, to gain hands-on experience on the practical aspects of neutron-instrument design and the requisite neutron-transport simulations. To date, these activities have resulted in a joint MEng thesis as well as a number of publications and contributions to national and international conferences. Building upon these previous works, the primary aim of this report is to provide a self-contained discussion of general criteria for instrument selection at ESS-Bilbao, the first accelerator-driven, low-energy neutron source designed in Spain. To this end, Chapter 1 provides a brief overview of the current design parameters of the accelerator and target station. Neutron moderation is covered in Chapter 2, where we take a closer look at two possible target-moderator-reflector configurations and pay special attention to the spectral and temporal characteristics of the resulting neutron pulses. This discussion provides a necessary starting point to assess the operation of ESSB in short- and long-pulse modes. These considerations are further explored in Chapter 3, dealing with the primary characteristics of ESS-Bilbao as a short- or long-pulse facility in terms of accessible dynamic range and spectral resolution. Other practical aspects including background suppression and the use of fast choppers are also discussed. The guiding principles introduced in the first three chapters are put to use in Chapter 4 where we analyse in some detail the capabilities of a small-angle scattering instrument, as well as how specific scientific requirements can be mapped onto the optimal use of ESS-Bilbao for condensed-matter research. Part 2 of the report contains additional supporting documentation, including a description of the ESSB McStas component, a detailed characterisation of moderator response and neutron pulses, and estimates ofparameters associated with the design and operation of neutron choppers. In closing this brief foreword, we wish to thank both ESS-Bilbao and ISIS for their continuing encouragement and support along the way.

A knowledge based application for industrialization design

After being designed, a product has to be manufactured, which means converting concepts and information into a real, physical object. This requires a big amount of resources and a careful planning. The product manufacturing must be designed too, and that is called Industrialization Design. An accepted methodology for this activity is starting defining simple structures and then progressively increasing the detail degree of the manufacturing solution. The impact of decisions taken at first stages of Industrialization Design is remarkable, and software tools to assist designers are required. In this paper a Knowledge Based Application prototype for the Industrialization Design is presented. The application is implemented within the environment CATIA V5/DELMIA. A case study with a simple Product from aerospace sector illustrates the prototype development.

Proposal for the Conceptual Design of Aeronautical Final Assembly Lines Based on the Industrial Digital Mock-Up Concept

The design of a Final Assembly Line (FAL) is carry out in the product industrialization activity. The phase dealing with the definition of conceptual solutions is characterized by depending heavily on the personnel experience and being time-consuming. To enhance such process, it is proposed a development of a knowledge based software application to assist designers in the definition of scenarios and to generate conceptual FAL alternatives. Both the scenario and the generated FAL solution are part of the industrialization digital mock-up (IDMU). A commercial software application used in the aircraft programmes and supporting the IDMU concepts of: Product, Process and Resource; was selected to implement a software prototype. This communication presents the adopted methodological approach and the architecture of the developed application.

A visual framework to accelerate knowledge discovery based on dimensionality reduction minimizing degradation of quality

Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.

Agent-based modeling and simulation for the design of the future european Air Traffic Management system: the experience of CASSIOPEIA

The SESAR (Single European Sky ATM Research) program is an ambitious re-search and development initiative to design the future European air traffic man-agement (ATM) system. The study of the behavior of ATM systems using agent-based modeling and simulation tools can help the development of new methods to improve their performance. This paper presents an overview of existing agent-based approaches in air transportation (paying special attention to the challenges that exist for the design of future ATM systems) and, subsequently, describes a new agent-based approach that we proposed in the CASSIOPEIA project, which was developed according to the goals of the SESAR program. In our approach, we use agent models for different ATM stakeholders, and, in contrast to previous work, our solution models new collaborative decision processes for flow traffic management, it uses an intermediate level of abstraction (useful for simulations at larger scales), and was designed to be a practical tool (open and reusable) for the development of different ATM studies. It was successfully applied in three stud-ies related to the design of future ATM systems in Europe.

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

Modeling Commercial Knowledge to Develop Advanced Agent-based Marketplaces for E-commerce

This paper argues about the utility of advanced knowledge-based techniques to develop web-based applications that help consumers in finding products within marketplaces in e-commerce. In particular, we describe the idea of model-based approach to develop a shopping agent that dynamically configures a product according to the needs and preferences of customers. Finally, the paper summarizes the advantages provided by this approach.

Using Electronic Documents for Knowledge Acquisition and Model Maintenance

Knowledge acquisition and model maintenance are key problems in knowledge engineering to improve the productivity in the development of intelligent systems. Although historically a number of technical solutions have been proposed in this area, the recent experience shows that there is still an important gap between the way end-users describe their expertise and the way intelligent systems represent knowledge. In this paper we propose an original way to cope with this problem based on electronic documents. We propose the concept of intelligent document processor as a tool that allows the end-user to read/write a document explaining how an intelligent system operates in such a way that, if the user changes the content of the document, the intelligent system will react to these changes. The paper presents the structure of such a document based on knowledge categories derived from the modern knowledge modeling methodologies together with a number of requirements to be understandable by end-users and problem solvers.