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Automated vehicles are entering the roads and automation is applied to cars, trucks, buses, and even motorcycles today. High automation foresees transitions during driving in both directions. The driver and rider state become a critical parameter since reliable automation allows safe intervention and transit control to the automation when manual driving is not performed safely anymore. When the control transits from automation to manual an appropriate driver state needs to be identified before releasing the automated control. The detection of driver states during manual and automated driving and an appropriate design of the human-machine interaction (HMI) are crucial steps to support these transitions. State‐of‐the‐art systems do not take the driver state, personal preferences, and predictions of road conditions into account. The ADAS&ME project, funded by the H2020 Programme of the European Commission, proposes an innovative and fully adaptive HMI framework, able to support driver/rider state monitoring‐based transitions in automated driving. The HMI framework is applied in the target vehicles: passenger car, truck, bus, and motorcycle, and in seven different use cases.

The concern of interaction or collaboration between components can be found when evolution of software engineering came a long way from machine-level language to procedural programming and then to object-oriented programming and now to component-based software development. An interaction is a set of activities that happens for a specific use case in a system, based on the ability of components (requires and provides services) to send messages to each other. This study introduces Component Interaction Markup Language (CIML) as an improvement of the attachment uses by mediator connector we proposed in earlier study. CIML aims to make the attachment well-formed as a generic framework for component composition based on interactions between components. CIML supports component composition based on interactions between components and has language constructs for description of component instantiations, component initializations and component interactions.

In the recent years, researchers in IT and business have become interested in Enterprise architecture (EA) increasingly. One reason for this growing interest is the wide range of benefits associated with EA. The review's main goals are to examine the status and progress of EA research in the world from 2005 to 2014; to provide other researchers with an extensive review which makes their paths easier in relevant studies; and to propose areas for future studies within this area. Analyses are carried out on the papers published in various journals during 10 years in EA studies. 120 papers were collected. For each article, the paper investigates distribution of collected papers in terms of time, journal, topics, author's institutional affiliation, university and country. Findings suggested that EA is receiving more attention from scholars over time and the number of published papers peaked in 2012. A significant amount of papers kept focused on modeling and usage. Furthermore, the main contributing factor to EA is university and the majority of papers belong to the United States of America (the U.S.A), followed by Sweden. The journal of Information Systems and e-Business Management published most papers in EA. Based on reviewing the existing literature, there are very few studies focusing on reviewing EA and one could not find any systematic literature review in the field of Enterprise Architecture during the last decade; therefore, to bridge the gap we decided to conduct this systematic literature review for Enterprise architecture.

Feature ranking is one of the basic methods in feature selection to select a subset of the original features. This paper uses a fuzzy clustering algorithm and proposes a new criterion for ranking the features. The importance of features is evaluated via the density function that is calculated in subtractive clustering. The proposed algorithm is tested over several well-known benchmark datasets. The performance of the proposed algorithm is also compared with some common algorithms. The results show that the proposed method is comparable to the other methods in term of obtained classification accuracy.

One of the main challenges in smart grids is synchronicity between generators and the controls. This synchronisation can be conducted by developing communications networks for smart grids. In case of having a large network, the optimum communication network design can be stated as an NP-hard problem with many possibilities. Traditional design methods might not work properly in reasonable time with acceptable computational complexity for such systems. This paper utilises graph theory to map the communication network to a graph problem. Then, a combination of fuzzy system (FS) and ant colony system (ACS), called fuzzy ant colony system (FACS), is proposed for optimisation of above graph with given constraints for synchronisation of smart power grids. Simulations versus exhaustive search and Rayleigh quotient approximation methods for the 39-bus New England power system present feasibility and effectiveness of our method for optimum communication network design in especially large scale smart power grids.