Abstract
The current market's demand for customization and responsiveness is a major challenge for producing intelligent, adaptive manufacturing systems. The Multi-Agent System (MAS) paradigm offers an alternative way to design this kind of system based on decentralized control using distributed, autonomous agents, thus replacing the traditional centralized control approach. The MAS solutions provide modularity, flexibility and robustness, thus addressing the responsiveness property, but usually do not consider true adaptation and re-configuration. Understanding how, in nature, complex things are performed in a simple and effective way allows us to mimic nature's insights and develop powerful adaptive systems that able to evolve, thus dealing with the current challenges imposed on manufacturing systems. The paper provides an overview of some of the principles found in nature and biology and analyses the effectiveness of bio-inspired methods, which are used to enhance multi-agent systems to solve complex engineering problems, especially in the manufacturing field. An industrial automation case study is used to illustrate a bio-inspired method based on potential fields to dynamically route pallets.

Abstract
The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.

Abstract
Permutation tests have extensively been used to estimate the significance of classification. Permutation tests usually use the test error as a dataset statistic to measure the difference between two or more populations. Then, to estimate the p-value(s), the test error is compared to a set of permuted test-error(s), which is usually obtained after permuting the labels of the populations. In this study, we investigate how several dataset factors, e.g., the number of samples, the number of classes, and the dimensionality size, may affect the p-value obtained via permutation tests. We performed the analysis using the standard permutation test procedure that uses the overall all test error dataset statistic and compared it to the permutation test procedure that uses per-class test error as a dataset statistic that we recently have proposed (doi:10.1016/j.neucom.2011.11.007). We found that permutation tests that use a per-class test error as a dataset statistic are not only more reliable in addressing the null hypothesis but also are highly sensitive to changes in the dataset factors that we investigated in this work. An important finding of this study is that when the dimensionality is low and the number of classes is up to several, say ten, highly above chance accuracy would be required to state the significance. For the same low dimensionality, however, slightly above chance accuracy would be adequate to state significance in a two-class problem.

Abstract
Simulation is a very useful tool to gather new information about an implemented model, because it can run artificial environments instead of putting in risk some entities that are influenced in the real process. The simulation of physical, chemical and biological processes in coastal ecosystems is used as a way to understand the system internal dynamics and to predict its evolution over time, in order to promote behaviors environmentally friendly and to induce effective and efficient management of the ecosystem as a whole. However, there are several ways of translating and interpreting the data provided by the simulation such as applying appropriate data mining models. This paper describes an approach that uses a Decision Tree model to produce intuitive information about the influence of several environmental variables on the growth conditions of bivalve species within an aquaculture exploration in a coastal ecosystem. This information is captured by relating the values of simulated variables, like water temperature or organic matter, with the length of the bivalve's shell, extrapolating information about the organic or physical conditions that increase or decrease the growth of the bivalve species, and guiding the stakeholders to locations for the best practice of the seeding process.

Abstract
In this paper we report on a methodology to model pedestrian behaviours whilst aggregate variables are concerned, with potential applications to different situations, such as evacuating a building in emergency events. The approach consists of using UWB (ultra-wide band) based data collection to characterise behaviour in specific scenarios. From a number of experiments carried out, we detail the single-file scenario to demonstrate the ability of this approach to represent macroscopic characteristics of the pedestrian flow. Results are discussed and we can conclude that UWB-based data collection shows great potential and suitability for human trajectory extraction, when compared to other traditional approaches.

Abstract
The use of Information and Communication Technologies (ICTs) has grown substantially over the past few years. However, a portion of the world's society has not been able to keep up with these technological advances. For this purpose, we present a serious game with a multi-touch interface envisioned to encourage and teach digitally excluded people on how to use the Portuguese Automated Teller Machine (ATM): a commodity much needed by society, but still avoided by some, mainly due to their fear of the digital world. An exploratory study was conducted to investigate if a serious game based on a new interaction paradigm can have a positive influence in the struggle against the Portuguese digital divide. We believe that the findings of our pilot case study can be useful to determine if a multi-touch serious game, due to its intuitiveness and ease of use, can stimulate the digitally excluded people to handle the ATM on a regular basis. The results that were obtained suggest that this approach may indeed produce a positive impact in the attempt to bridge the Portuguese digital divide.