Abstract

Abstract
One of the major data mining tasks is to cluster similar data, because of its usefulness, providing means of summarizing large ammounts of raw data into handy information. Clustering data streams is particularly challenging, because of the constraints imposed when dealing with this kind of input. Here we report our work, in which it was investigated the use of WiSARD discriminators as primary data synthesizing units. An analysis of StreamWiSARD, a new sliding-window stream data clustering system, the benefits and the drawbacks of its use and a comparison to other approaches are all presented. © 2012 Springer-Verlag.

Abstract
The transistor is an electronic component that revolutionized the world of electronics, enabling the development and improvement of various systems and products in this area over the years. The paper transistor resulted from research conducted by a team coordinated by Elvira Fortunato. It is an ultra-small (nano) transistor, which is paper-based, a cheap and easily accessible material. This article intends, first, to determine the innovation model behind the paper transistor and, second, based on a survey of a sample of Portuguese firms in industries inclined to adopting the transistor, to understand its level of implementation and assess the determinants that may be influencing this process. A review of relevant literature and an interview with Elvira Fortunato, the key researcher, support the conclusion that the innovation model in question is the interactive one. In fact, since the project began, significant interaction took place between research institutions and industry, which continued throughout the development process. In the second phase of our work, a group of firms was surveyed, selected on the basis of the relevance of the technology on the activities they conduct. Only one firm from the five respondents said they knew of the paper transistor. The answers collected also indicated that there are three main determinants which explain why firms have failed to adopt this transistor: the expected profit, the existence of networks between firms and universities, and information. Thus, we conclude that there is a significant need for increased interaction between universities and firms, so as to promote a broader understanding of the stakeholders' needs, with the development of innovations in universities and research institutes based on adaptation to the business context.

Abstract
Conceptualisation processes are pervasive to most technical and professional activities, but are seldom addressed explicitly due to the lack of theoretical and practical methods and tools. However, it seems not to be a popular research topic in knowledge representation or its sub-areas such as ontology engineering. The approach described in this paper is a contribution to the development of methods and tools to collaborative conceptualisation processes. The particularly challenging problem of conceptual negotiation is here tackled through a combination of ColBlend method and an argumentation-based strategy, creating an innovative method to conceptual negotiation, argile method. This method was implemented in to the ConceptME platform as an advanced negotiation mechanism. © 2012 Springer-Verlag.

Abstract
Computational methods used in microscopy cell image analysis have largely augmented the impact of imaging techniques, becoming fundamental for biological research. The understanding of cell regulation processes is very important in biology, and in particular confocal fluorescence imaging plays a relevant role for the in vivo observation of cells. However, most biology researchers still analyze cells by visual inspection alone, which is time consuming and prone to induce subjective bias. This makes automatic cell image analysis essential for large scale, objective studies of cells. While the classic approach for automatic cell analysis is to use image segmentation, for in vivo confocal fluorescence microscopy images of plants, such approach is neither trivial nor is it robust to image quality variations. To analyze plant cells in in vivo confocal fluorescence microscopy images with robustness and increased performance, we propose the use of local convergence filters (LCF). These filters are based in gradient convergence and as such can handle illumination variations, noise and low contrast. We apply a range of existing convergence filters for cell nuclei analysis of the Arabidopsis thaliana plant root tip. To further increase contrast invariance, we present an augmentation to local convergence approaches based on image phase information. Through the use of convergence index filters we improved the results for cell nuclei detection and shape estimation when compared with baseline approaches. Using phase congruency information we were able to further increase performance by 11% for nuclei detection accuracy and 4% for shape adaptation. Shape regularization was also applied, but with no significant gain, which indicates shape estimation was good for the applied filters.

Abstract
We extend the work of Bellare, Boldyreva and Staddon on the systematic analysis of randomness reuse to construct multi-recipient encryption schemes to the case where randomness is reused across different cryptographic primitives. We find that through the additional binding introduced through randomness reuse, one can actually obtain a security amplification with respect to the standard black-box compositions, and achieve a stronger level of security. We introduce stronger notions of security for encryption and signatures, where challenge messages can depend in a restricted way on the random coins used in encryption, and show that two variants of the KEM/DEM paradigm give rise to encryption schemes that meet this enhanced notion of security. We obtain the most efficient signcryption scheme to date that is secure against insider attackers without random oracles. © 2012 Springer-Verlag.