In January 2017, relations between Greece and Turkey were under severe strain when warships from both sides engaged in a brief standoff near a pair of uninhabited Greek ‘islets’ in the Aegean, whose sovereignty is disputed by Turkey. Theoretically informed by the literature of foreign policy analysis, we examine how the Greek diplomats, military officers and political analysts interpreted Turkey’s behaviour at that particular time. The article considers the following research question: which factors, from a Greek point of view, explain Turkey’s foreign policy in the Aegean in January 2017? Our theoretical expectation is that, in the aftermath of the coup attempt in Turkey, Greek diplomats, military officers and political analysts would ascribe domestic calculations into Turkey’s activities. We employed Q- methodology to uncover socially shared perspectives on this topic. Based on our findings, we uncovered two viewpoints: (1) Turkey’s diachronic strategy in the Aegean and (2) the strongman style. According to the former and most widely shared viewpoint, a consistent ‘rationalist’ strategy to change the status quo in the Aegean explains Turkey’s behaviour. According to the second one, the belief system of Turkey’s leadership legitimises the use of force in the conduct of foreign policy.
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his paper develops a new, broader, and more realistic lens to study (lacking) linkages between government policy and school practices. Drawing on recent work in organization theory, we advance notions on cluster of organization routines and the logic of complementarities underlying organizational change. This lens allows looking at how schools do (not) change a cluster of organization routines in response to multiple, simultaneous demands posed by government policies. Thirteen purposively selected Dutch secondary schools responding to three central government policies calling for concurrent change were analyzed, taking the schedule of a school as an exemplary case of a cluster of organization routines. Five distinct responses were distinguished, which can be sorted according to their impact on the whole organization. The study fnds that ten of the thirteen schools did not change anything in response to at least one of the three policies we studied. However, all schools changed their cluster of organization routines, which impacted the whole organization in response to at least one of the three government policies. Therefore, looking at combinations of responses and considering the impact of change on school organizations qualifes ideas about schools being resistant to policy or unwilling to change and improve.
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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.
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MUSE supports the CIVITAS Community to increase its impact on urban mobility policy making and advance it to a higher level of knowledge, exchange, and sustainability.As the current Coordination and Support Action for the CIVITAS Initiative, MUSE primarily engages in support activities to boost the impact of CIVITAS Community activities on sustainable urban mobility policy. Its main objectives are to:- Act as a destination for knowledge developed by the CIVITAS Community over the past twenty years.- Expand and strengthen relationships between cities and stakeholders at all levels.- Support the enrichment of the wider urban mobility community by providing learning opportunities.Through these goals, the CIVITAS Initiative strives to support the mobility and transport goals of the European Commission, and in turn those in the European Green Deal.Breda University of Applied Sciences is the task leader of Task 7.3: Exploitation of the Mobility Educational Network and Task 7.4: Mobility Powered by Youth Facilitation.
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
