Pattern analysis and prediction of sensory data is becoming an increasing scientific challenge and a massive economical interest supports the need for better pattern mining techniques. The aim of this paper is to investigate efficient mining of useful information from a sensor network representing an ambient intelligence environment. The goal is to extract and predict behavioral patterns of a p...

Especially in the knowledge intensive service industry and times of virtual teams, there is a high need to support collaboration and information exchange between employees with IT. Whereas many organizations have recognized the great potential of Enterprise Social Networks (ESN) in this context, there is still a lack of well-founded and applicable approaches to make this potential visible i.e. ...

In order to manage knowledge work, companies need to understand how knowledge is shared, integrated, translated and transformed in organisational practice. However, knowledge work often happens in informal organisational structures, thus, making it difficult to identify and understand the occurring knowledge practices and participating actors. Enterprise Social Networks (ESN), i.e. internally a...

Since the 2000s, social networks have grown spectacularly until they are now regarded as indispensable and introduced as a daily practice of millions of users. Enterprises have become aware of the need and the importance of these collaborative tools, and the concept of Enterprise Social Network (ESN) has now emerged. As such, OpenPaaS is an innovative ESN that aims at facilitating inter-organiz...

Echo state networks are powerful recurrent neural networks. However, they are often unstable and shaky, making the process of finding an good ESN for a specific dataset quite hard. Obtaining a superb accuracy by using the Echo State Network is a challenging task. We create, develop and implement a family of predictably optimal robust and stable ensemble of Echo State Networks via regularizing t...

Echo State Networks (ESN) have demonstrated their efficiency in supervised learning of time series: a ”reservoir” of neurons provide a set of dynamical systems that can be linearly combined to match the target dynamics, using a simple quadratic optimisation algorithm to tune the few free parameters. In an unsupervised learning context, however, another optimiser is needed. In this paper, an ada...

Temporal phasing analysis is integral to ubiquitous/“smart” coaching devices and sport science. This study presents a novel approach to autonomous temporal phasing of human motion from captured tennis activity (3D data, 66 time-series). Compared to the optimised Echo State Network (ESN) model achieving 85 % classification accuracy, the ESN ensemble system demonstrates improved classification of...

Abstract. The properties of the auroral electrojets are examined on basis a trained machine-learning model. relationships between solar-wind parameters and AU AL indices modeled with an echo state network (ESN), kind recurrent neural network. We can consider this ESN model to represent nonlinear effects inputs electrojets. To identify electrojets, we obtain various synthetic data by using artif...

HIV serodiscordant couples are an extremely useful tool for examining immune responses that may contribute to reduced transmission or protection from HIV infection. A homozygous 32-base pair deletion in the gene encoding the Chemokine receptor 5 protein (CCR5) is strongly associated with protection from HIV infection (Huang et al., 1996). In contrast, the contribution of humoral, cellular and i...