Driverless road-marking Machines: Ma(r)king the Way towards the Future of Mobility

Driverless road maintenance could potentially be highly beneficial to all its stakeholders, with the key goals being increased safety for all road participants, more efficient traffic management, and reduced road maintenance costs such that the standard of the road infrastructure is sufficient for it to be used in Automated Driving (AD). This paper addresses how the current state of technology could be expanded to reach those goals. Within the project 'System for Teleoperated Road-marking' (SToRM), using the road-marking machine as the system, different operation modes based on teleoperation were discussed and developed. Furthermore, a functional system overview considering both hardware and software elements was experimentally validated with an actual road-marking machine and should serve as a baseline for future efforts in this and similar areas.Comment: Accepted at 2022 IEEE International Conference on Systems, Man and Cybernetics (SMC

Using System Analysis and Personas for e-Health Interaction Design

Today, designers obtain more central roles in product and service development (Perks, Cooper, & Jones, 2005). They have to deal with increasingly complicated problems, like integrating the needs of various stakeholders while taking care about social, ethical and ecological consequences of their designs. To deal with this demanding design situation, they need to apply new methods to organize the available information and to negotiate the stakeholder’s perspectives. This paper describes how systems analysis supports the design process in a complex environment. In a case study, we demonstrate how this method enables designers to describe user requirements for complex design environments while considering the perspectives of various stakeholders. We present a design research project applying cybernetic systems analysis using the software ''System-Tools'' (Vester, 2002). Results from the analysis were taken to inform the design of an electronic patient record (EPR), considering the particularities of the German health care system. Based on the analysis, we developed a set of requirements for every stakeholder group, detailing the patients' perspective with persona descriptions. We then picked a main persona as reference for the EPR design. We describe the resulting design sketch and discuss the value of cybernetic systems analysis as a tool to deal with complex social environments. The result shows how the method helps designers to structure and organize information about the context and identify fruitful intervention opportunities for design. Keywords: E-Health; System Analysis, Cybernetics; Personas.</p

Class decomposition for GA-based classifier agents – A Pitt approach

Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental learning with statistical algorithms or neural networks, rather than evolutionary algorithms. The work in this paper employs genetic algorithms (GAs) as basic learning algorithms for incremental learning within one or more classifier agents in a multi-agent environment. Four new approaches with different initialization schemes are proposed. They keep the old solutions and use an “integration” operation to integrate them with new elements to accommodate new attributes, while biased mutation and crossover operations are adopted to further evolve a reinforced solution. The simulation results on benchmark classification data sets show that the proposed approaches can deal with the arrival of new input attributes and integrate them with the original input space. It is also shown that the proposed approaches can be successfully used for incremental learning and improve classification rates as compared to the retraining GA. Possible applications for continuous incremental training and feature selection are also discussed

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon