Improving the learning experience and learning environment of adults in Higher Education – Project LIHE: the Portuguese case

Project LIHE: the Portuguese Case. ESREA Fourth Access Network Conference – “Equity, Access and Participation: Research, Policy and Practice”. Edinburgh (Scotland), 11 – 13 December, 2003.

The verification of temporal KBS: SPARSE - a case study in power systems

In this paper we present VERITAS, a tool that focus time maintenance, that is one of the most important processes in the engineering of the time during the development of KBS. The verification and validation (V&V) process is part of a wider process denominated knowledge maintenance, in which an enterprise systematically gathers, organizes, shares, and analyzes knowledge to accomplish its goals and mission. The V&V process states if the software requirements specifications have been correctly and completely fulfilled. The methodologies proposed in software engineering have showed to be inadequate for Knowledge Based Systems (KBS) validation and verification, since KBS present some particular characteristics. VERITAS is an automatic tool developed for KBS verification which is able to detect a large number of knowledge anomalies. It addresses many relevant aspects considered in real applications, like the usage of rule triggering selection mechanisms and temporal reasoning.

An intelligent tutoring approach to support students and technicians in electrical installation design

Designing electric installation projects, demands not only academic knowledge, but also other types of knowledge not easily acquired through traditional instructional methodologies. A lot of additional empirical knowledge is missing and so the academic instruction must be completed with different kinds of knowledge, such as real-life practical examples and simulations. On the other hand, the practical knowledge detained by the most experienced designers is not formalized in such a way that is easily transmitted. In order to overcome these difficulties present in the engineers formation, we are developing an Intelligent Tutoring System (ITS), for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students.

Intelligent power system

Artificial intelligence techniques are being widely used to face the new reality and to provide solutions that can make power systems undergo all the changes while assuring high quality power. In this way, the agents that act in the power industry are gaining access to a generation of more intelligent applications, making use of a wide set of AI techniques. Knowledge-based systems and decision-support systems have been applied in the power and energy industry. This article is intended to offer an updated overview of the application of artificial intelligence in power systems. This article paper is organized in a way so that readers can easily understand the problems and the adequacy of the proposed solutions. Because of space constraints, this approach can be neither complete nor sufficiently deep to satisfy all readers’ needs. As this is amultidisciplinary area, able to attract both software and computer engineering and power system people, this article tries to give an insight into themost important concepts involved in these applications. Complementary material can be found in the reference list, providing deeper and more specific approaches.

Society and technological evolution: challenges and opportunities

Starting from the assumption that, the organizational learning process influences, in a positive way, the innovative environment and that it shows positive effects on individual, group and organizational performance, this paper deals with the analysis of companies that provide knowledge-intensive products. Referring to the initial information obtained through an adequate survey that is still being performed since May 2009, the main goal is to identify the ways to an organizational learning, measure its importance and identify the effects on the social and economic development. Our reflexion study handles two Portuguese knowledge-rich-organizations, based on the metropolitan area of Lisbon. The paper has the following methodological structure: in the first chapter we will make a theoretical contextualization about the organizational learning; in the second chapter we will handle the data recovered using the SPSS statistics software and, afterwards, presenting the main results. Finally, starting from the main conclusions achieved, we willgive clues to an ongoing reflection.

The economics of language or how can language be an asset? General reflections on the European case and brief focus on the case of portuguese

In this paper, we will focus on the importance of languages as an asset to people and companies in knowledge-based society, giving special attention to the case of portuguese, not forgetting the role of Higher Education Institutions in preparing students to be part of the new creative multilingual and sucsessful class.

Licensing endogenous cost-reduction in a differentiated Stackelberg model

In this paper we consider a differentiated Stackelberg model, when the leader firm engages in an R&D process that gives an endogenous cost-reducing innovation. The aim is to study the licensing of the cost-reduction by a two-part tariff. By using comparative static analysis, we conclude that the degree of the differentiation of the goods plays an important role in the results. We also do a direct comparison between our model and Cournot duopoly model.

ESEIG Mobile: an m-learning approach in a superior school

In recent years, mobile learning has emerged as an educational approach to decrease the limitation of learning location and adapt the teaching-learning process to all type of students. However, the large number and variety of Web-enabled devices poses challenges for Web content creators who want to automatic get the delivery context and adapt the content to mobile devices. This paper studies several approaches to adapt the learning content to mobile phones. It presents an architecture for deliver uniform m-Learning content to students in a higher School. The system development is organized in two phases: firstly enabling the educational content to mobile devices and then adapting it to all the heterogeneous mobile platforms. With this approach, Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.

Photoluminescence and electrical study of fluctuating potentials in Cu2ZnSnS4-based thin films

In this work, we investigated structural, morphological, electrical, and optical properties from a set of Cu2ZnSnS4 thin films grown by sulfurization of metallic precursors deposited on soda lime glass substrates coated with or without molybdenum. X-ray diffraction and Raman spectroscopy measurements revealed the formation of single-phase Cu2ZnSnS4 thin films. A good crystallinity and grain compactness of the film was found by scanning electron microscopy. The grown films are poor in copper and rich in zinc, which is a composition close to that of the Cu2ZnSnS4 solar cells with best reported efficiency. Electrical conductivity and Hall effect measurements showed a high doping level and a strong compensation. The temperature dependence of the free hole concentration showed that the films are nondegenerate. Photoluminescence spectroscopy showed an asymmetric broadband emission. The experimental behavior with increasing excitation power or temperature cannot be explained by donor-acceptor pair transitions. A model of radiative recombination of an electron with a hole bound to an acceptor level, broadened by potential fluctuations of the valence-band edge, was proposed. An ionization energy for the acceptor level in the range 29–40 meV was estimated, and a value of 172 ±2 meV was obtained for the potential fluctuation in the valence-band edge.

Accounting education in an action-based learning environment: lessons learned

In the context of the Bologna Declaration a change is taking place in the teaching/learning paradigm. From teaching-centered education, which emphasizes the acquisition and transmission of knowledge, we now speak of learning-centered education, which is more demanding for students. This paradigm promotes a continuum of lifelong learning, where the individual needs to be able to handle knowledge, to select what is appropriate for a particular context, to learn permanently and to understand how to learn in new and rapidly changing situations. One attempt to face these challenges has been the experience of ISCAP regarding the teaching/learning of accounting in the course Managerial Simulation. This paper describes the process of teaching, learning and assessment in an action-based learning environment. After a brief general framework that focuses on education objectives, we report the strengths and limitations of this teaching/learning tool. We conclude with some lessons from the implementation of the project.

Innovation through virtual communities of Practice: motivation and constraints in the knowledge-creation process

Communities of Practice are places which provide a sound basis for organizational learning, enabling knowledge creation and acquisition thus improving organizational performance, leveraging innovation and consequently increasing competitively. Virtual Communities of Practice (VCoP‟s) can perform a central role in promoting communication and collaboration between members who are dispersed in both time and space. The ongoing case study, described here, aims to identify both the motivations and the constraints that members of an organization experience when taking part in the knowledge creating processes of the VCoP‟s to which they belong. Based on a literature review, we have identified several factors that influence such processes; they will be used to analyse the results of interviews carried out with the leaders of VCoP‟s in four multinationals. As future work, a questionnaire will be developed and administered to the other members of these VCoP‟s

Knowledge and technologies in innovative information systems

7th Mediterranean Conference on Information Systems, MCIS 2012, Guimaraes, Portugal, September 8-10, 2012, Proceedings Series: Lecture Notes in Business Information Processing, Vol. 129

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

Histogram-based DNA analysis for the visualization of chromosome, genome and species information

We describe a novel approach to explore DNA nucleotide sequence data, aiming to produce high-level categorical and structural information about the underlying chromosomes, genomes and species. The article starts by analyzing chromosomal data through histograms using fixed length DNA sequences. After creating the DNA-related histograms, a correlation between pairs of histograms is computed, producing a global correlation matrix. These data are then used as input to several data processing methods for information extraction and tabular/graphical output generation. A set of 18 species is processed and the extensive results reveal that the proposed method is able to generate significant and diversified outputs, in good accordance with current scientific knowledge in domains such as genomics and phylogenetics.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.