Abstract

Abstract
This paper presents a Swarm based Cooperation Mechanism for scheduling optimization. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to support decision making in agile manufacturing environments. Agents coordinate their actions automatically without human supervision considering a common objective - global scheduling solution taking advantages from collective behavior of species through implicit and explicit cooperation. The performance of the cooperation mechanism will be evaluated consider implicit cooperation at first stage through ACS, PSO and ABC algorithms and explicit through cooperation mechanism application.

Abstract
The development of avionics systems is typically a tedious and cumbersome process. In addition to the required functions, developers must consider various and often conflicting non-functional requirements such as safety, performance, and energy efficiency. Certainly, an integrated approach with a seamless design flow that is capable of requirements modelling and supporting refinement down to an actual implementation in a traceable way, may lead to a significant acceleration of development cycles. This paper presents an aspect-oriented approach supported by a toolchain that deals with functional and non-functional requirements in an integrated manner. It also discusses how the approach can be applied to development of safety-critical systems and provides experimental results.

Abstract
In this work we analyze the evolving dynamics of different strategies of collaborative networks that emerge from the creation and diffusion of knowledge. An evolutionary economic approach is adopted by introducing decision rules that are applied routinely and an agent-based model is developed. Firms (the agents) can collaborate and create networks for research and development purposes. We have compared three collaboration strategies (A-peer-to-peer complementariness, B-concentration process and C-virtual cooperation networks) that were defined on the basis of literature and on empirical evidence. Strategies are introduced exogenously in the simulation. The aims of this paper are twofold: (i) to analyze the importance of the networking effects; and (ii) to test the differences among collaboration strategies. It was possible to conclude that profit is associated with higher stock of knowledge and with smaller network diameter. In addition, concentration strategies are more profitable and more efficient in transmitting knowledge through the network. These processes reinforce the stock of knowledge and the profit of the firms located in the centers of the networks.

Abstract
Leishmania is a unicellular parasite that infects mammals. Biologists are interested in determining the effect of drugs in Leishmania infections. This requires the manual annotation of the number of macrophages and parasites in images, in order to obtain the percentage of infection (PI), the average number of parasites per infected cell (NPI) and the infection index (IX). Considering that manual annotation is tedious, time-consuming and often erroneous, in this paper we propose an automatic method for automatic annotation of Leishmania infections using fluorescence microscopy. Moreover, when compared to related works, the proposed method is able to get superior performance under most perspectives.

Abstract
We present a novel approach to 6D visual odometry for vehicles with calibrated stereo cameras. A dense probabilistic egomotion (5D) method is combined with robust stereo feature based approaches and Extended Kalman Filtering (EKF) techniques to provide high quality estimates of vehicle's angular and linear velocities. Experimental results show that the proposed method compares favorably with state-the-art approaches, mainly in the estimation of the angular velocities, where significant improvements are achieved.