Over the last years a large growth in Electric Vehicles (EV) and charging infrastructure (CI) development has been observed. Particularly in metropolitan areas this growth has led to a system in which multitudes of interactions between EV users take place. While many researchers have focused on EV user charging behavior and deployment strategies for CI, little attention has been paid to conceptualizing the problem domain. This research provides a brief overview of complex systems theory, and derives six characterizing elements of complex systems that may be applicable for CI. The paper investigates both theoretically but also empirically how these characterizing elements apply for CI and provides implications for the further roll-out of CI for both policy makers and researchers. We illustrate our findings with preliminary results form ongoing research. Recommendations include the further development of simulation tools that are capable of exploring effects of e.g. non-linear behavior, feedback loops and emergence of new patterns on CI performance. In the end this paper aims to provide directions to enable policy makers to be better prepared for the anticipated exponential growth of EVs and CI.
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In many European cities, urban experimentation is increasingly preferred as a method for testing and disseminating innovations that might ignite a transformation toward more sustainable cities. By both academics and practitioners, these experiments tend to be approached as relatively neutral initiatives through which plural urban stakeholders willfully collaborate, while their success is seen as above all dependent on effective management. For this reason, the political nature of urban experiments, in the sense that they entangle different and often contending stakeholders in their innovation processes, remains relatively unarticulated in both practice and the academic literature. Building on the urban experimentation literature and political theory, this conceptual paper argues that the depoliticization of experimental initiatives is especially problematic for unleashing their transformative potential, which requires revealing the existing power-relations and biases keeping the status-quo in place and negotiability of radical alternatives. From this perspective, the paper sketches out four ideal-typical trajectories for experiments as related to their (de)politicization; optimization, blind leap, antagonistic conflict and transformation. Bringing insights from political theory to bear on the urban experimentation literature, we proceed to hypothesize the implications of our ideal-types for urban experiments’ transformative capacities. The paper closes by presenting a future research and policy agenda.
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The security of online assessments is a major concern due to widespread cheating. One common form of cheating is impersonation, where students invite unauthorized persons to take assessments on their behalf. Several techniques exist to handle impersonation. Some researchers recommend use of integrity policy, but communicating the policy effectively to the students is a challenge. Others propose authentication methods like, password and fingerprint; they offer initial authentication but are vulnerable thereafter. Face recognition offers post-login authentication but necessitates additional hardware. Keystroke Dynamics (KD) has been used to provide post-login authentication without any additional hardware, but its use is limited to subjective assessment. In this work, we address impersonation in assessments with Multiple Choice Questions (MCQ). Our approach combines two key strategies: reinforcement of integrity policy for prevention, and keystroke-based random authentication for detection of impersonation. To the best of our knowledge, it is the first attempt to use keystroke dynamics for post-login authentication in the context of MCQ. We improve an online quiz tool for the data collection suited to our needs and use feature engineering to address the challenge of high-dimensional keystroke datasets. Using machine learning classifiers, we identify the best-performing model for authenticating the students. The results indicate that the highest accuracy (83%) is achieved by the Isolation Forest classifier. Furthermore, to validate the results, the approach is applied to Carnegie Mellon University (CMU) benchmark dataset, thereby achieving an improved accuracy of 94%. Though we also used mouse dynamics for authentication, but its subpar performance leads us to not consider it for our approach.
SOCIO-BEE proposes that community engagement and social innovation combined with Citizen Science (CS) through emerging technologies and playful interaction can bridge the gap between the capacity of communities to adopt more sustainable behaviours aligned with environmental policy objectives and between the citizen intentions and the real behaviour to act in favour of the environment (in this project, to reduce air pollution). Furthermore, community engagement can raise other citizens’ awareness of climate change and their own responses to it, through experimentation, better monitoring, and observation of the environment. This idea is emphasised in this project through the metaphor of bees’ behaviour (with queens, working and drone bees as main CS actors), interested stakeholders that aim at learning from results of CS evidence-based research (honey bears) and the Citizen Science hives as incubators of CS ideas and projects that will be tested in three different pilot sites (Ancona, Marousi and Ancona) and with different population: elderly people, everyday commuters and young adults, respectively. The SOCIO-BEE project ambitions the scalable activation of changes in citizens’ behaviour in support of pro-environment action groups, local sponsors, voluntary sector and policies in cities. This process will be carried out through low-cost technological innovations (CS enablers within the SOCIO BEE platform), together with the creation of proper instruments for institutions (Whitebook and toolkits with recommendations) that will contribute to the replication, upscaling, massive adoption and to the duration of the SOCIO-BEE project. The solution sustainability and maximum outreach will be ensured by proposing a set of public-private partnerships.For more information see the EU-website.
