Manual crack inspection is labor-intensive and impractical at scale, prompting a shift toward AI-based segmentation methods. We present a novel crack segmentation model that leverages the Segment Anything Model 2 (SAM 2) through transfer learning to detect cracks on masonry surfaces. Unlike prior approaches that rely on encoders pretrained for image classification, we fine-tune SAM 2, originally trained for segmentation tasks, by freezing its Hiera encoder and FPN neck, while adapting its prompt encoder, LoRA matrices, and mask decoder for the crack segmentation task. No prompt input is used during training to avoid detection overhead. Our aim is to increase robustness to noise and enhance generalizability across different surface types. This work demonstrates the potential of foundational segmentation models in enabling more reliable and field-ready AI-based crack detection tools.
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Municipalities play an important role in tackling city logistics related matters, having many instruments at hand. However, it is not self-evident that all municipalities use these instruments to their full potential. A method to measure city logistics performance of municipalities can help in creating awareness and guidance, to ultimately lead to a more sustainable environment for inhabitants and businesses. Subsequently, this research is focused on a maturity model as a tool to assess the maturity level of a municipality for its performance related city logistics process management. Various criteria for measuring city logistics performance are studied and based on that the model is populated through three focus fields (Technical, Social and Corporate, and Policy), branching out into six areas of development: Information and communication technology, urban logistics planning, Stakeholder communication, Public Private Partnerships, Subsidisation and incentivisation, and Regulations. The CL3M model was tested for three municipalities, namely, municipality of Utrecht, Den Bosch and Groningen. Through these maturity assessments it became evident the model required specificity complementary to the existing assessment interview, and thus a SWOT analysis should be added as a conclusion during the maturity assessment.
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This study furthers game-based learning for circular business model innovation (CBMI), the complex, dynamic process of designing business models according to the circular economy principles. The study explores how game-play in an educational setting affects learning progress on the level of business model elements and from the perspective of six learning categories. We experimented with two student groups using our game education package Re-Organise. All students first studied a reader and a game role description and then filled out a circular business model canvas and a learning reflection. The first group, i.e., the game group, updated the canvas and the reflection in an interactive tutorial after gameplay. The control group submitted their updated canvas and reflection directly after the interactive tutorial without playing the game. The results were analyzed using text-mining and qualitative methods such as word co-occurrence and sentiment polarity. The game group created richer business models (using more waste processing technologies) and reflections with stronger sentiments toward the learning experience. Our detailed study results (i.e., per business model element and learning category) enhance understanding of game-based learning for circular business model innovation while providing directions for improving serious games and accompanying educational packages.
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In this mixed methods study, a moderated mediation model predicting effects of leader-member exchange (LMX) and organizational citizenship behaviors (OCB) on innovative work behaviors, with employability as a mediator, has been tested. Multi-source data from 487 pairs of employees and supervisors working in 151 small and medium-sized enterprises (SMEs) supported our hypothesized model. The results of structural equation modelling provide support for our model. In particular, the benefits of close relationships and high-quality exchanges between employee and supervisor (LMX), and fostering individual development as a result of employees’ OCB have an indirect effect on innovative work behaviors through positive effects on workers’ employability. Innovative work behaviors depend on employees’ knowledge, skills, and expertise. In other words, enhancing workers’ employability nurtures innovative work behaviors. In addition, we found a moderation effect of organizational politics on the relationship between employability and innovative work behaviors. Secondly, qualitative methods focusing on experiences of the antecedents and outcomes of employability were used to complement our quantitative results. All in all, this study has important consequences for managerial strategies and practices in SMEs and call for an awareness of the dysfunctional effect of perceived organizational politics.
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This paper presents a comprehensive study on assisting new AI programmers in making responsible choices while programming. The research focused on developing a process model, incorporating design patterns, and utilizing an IDE-based extension to promote responsible Artificial Intelligence (AI) practices. The experiment evaluated the effectiveness of the process model and extension, specifically examining their impact on the ability to make responsible choices in AI programming. The results revealed that the use of the process model and extension significantly enhanced the programmers' understanding of Responsible AI principles and their ability to apply them in code development. These findings support existing literature highlighting the positive influence of process models and patterns on code development capabilities. The research further confirmed the importance of incorporating Responsible AI values, as asking relevant questions related to these values resulted in responsible AI practices. Furthermore, the study contributes to bridging the gap between theoretical knowledge and practical application by incorporating Responsible AI values into the centre stage of the process model. By doing so, the research not only addresses the existing literature gap, but also ensures the practical implementation of Responsible AI principles.
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We aim to understand how actors respond to field logic plurality and maintain legitimacy through business model innovation. Drawing on a longitudinal field study in the fashion industry, we traced how de novo and incumbent firms incorporate circular logics in business models (for sustainability) and uncover how the intersection between issue and exchange fields creates institutional complexity and experimental spaces for business model innovation. Our findings showed a shift in the discourse on circular logic that diverted attention and resources from materials innovation (e.g., recycling) to business model innovation (e.g., circular business models). By juxtaposing institutional complexity and external pressure to maintain legitimacy, we derived four strategic business model innovation responses—preserve, detach, integrate and extend—that illuminate how actors leverage shifting logics and innovate extant business models (for sustainability). We make novel contributions to the literature on organizational fields, business models for sustainability, and business model innovation.
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Essay based on a Presentation to International Stakeholder Forum, Convened by the Board of Directors of the Fair Labor Association, Washington D.C. June 26, 2009. There is much concern about the current crisis. Indeed the fall in consumption in developed countries is steep, anything between 15 to 25% over the first months of 2009 in most countries. This is double the decline of sales in previous recessions. However to this cyclical crisis and concerns two new concerns are being added. The first new concern to fashion, mainly amongst retailers and brands, is related to their impact on manufacturing in developing countries and to the employment and social conditions of workers. The second concern new to fashion, which is broadly shared amongst industries, is that after the crisis more structural changes in consumption will happen.
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this thesis was simply a research done to see how the manor amsterdam can use technologies to enhance its guest eperience. Surveys and intervews were conducted to see what the guest preferences were after which an implementation process was also drawn up.
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Third chapter of the English version of the book 'Energieke Arbeid' published by the Centre of Applied Labour Market Research and Innovation (Dutch abbreviation: KCA) to celebrate the 10th anniversary of applied labour market research at Hanze University of Applied Sciences. This chapter discusses the second line of research of KCA: The Labour Market in the EnergyPort Groningen Region.
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Globally, coastal areas can be seen as the most popular tourist-recreational destinations. Consequently, these destinations generate major visitor flows. Furthermore, they are interpreted differently by every visitor, for example depending on lifestyles and age. These two problems, or maybe chances, are the central focus in this article. More specifically, this conceptual paper examines what the typical coastal experience consists of and in which ways the producers of the tourist-recreational coastal product can anticipate this. After explaining the principles of visitor management, as defined by Ennen, a theoretical framework is presented that tries to capture the total coastal experience. Then, two existing coastal areas are projected onto this framework. Finally, some conclusions are drawn.
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