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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Masonry structures represent the highest proportion of building stock worldwide. Currently, the structural condition of such structures is predominantly manually inspected which is a laborious, costly and subjective process. With developments in computer vision, there is an opportunity to use digital images to automate the visual inspection process. The aim of this study is to examine deep learning techniques for crack detection on images from masonry walls. A dataset with photos from masonry structures is produced containing complex backgrounds and various crack types and sizes. Different deep learning networks are considered and by leveraging the effect of transfer learning crack detection on masonry surfaces is performed on patch level with 95.3% accuracy and on pixel level with 79.6% F1 score. This is the first implementation of deep learning for pixel-level crack segmentation on masonry surfaces. Codes, data and networks relevant to the herein study are available in: github.com/dimitrisdais/crack_detection_CNN_masonry.
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An illustrative non-technical review was published on Towards Data Science regarding our recent Journal paper “Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning”.While new technologies have changed almost every aspect of our lives, the construction field seems to be struggling to catch up. Currently, the structural condition of a building is still predominantly manually inspected. In simple terms, even nowadays when a structure needs to be inspected for any damage, an engineer will manually check all the surfaces and take a bunch of photos while keeping notes of the position of any cracks. Then a few more hours need to be spent at the office to sort all the photos and notes trying to make a meaningful report out of it. Apparently this a laborious, costly, and subjective process. On top of that, safety concerns arise since there are parts of structures with access restrictions and difficult to reach. To give you an example, the Golden Gate Bridge needs to be periodically inspected. In other words, up to very recently there would be specially trained people who would climb across this picturesque structure and check every inch of it.
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This paper outlines an investigation into the updating of fatigue reliability through inspection data by means of structural correlation. The proposed methodology is based on the random nature of fatigue fracture growth and the probability of damage detection and introduces a direct link between predicted crack size and inspection results. A distinct focus is applied on opportunities for utilizing inspection information for the updating of both inspected and uninspected (or uninspectable) locations.
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Few people I know act likea magnet in the way Laura does. If you hear her speak, see her move, enjoy her smile - you can't help but want to be a part of what makes her heart beat faster. She radiates passion for her dream topic biomimicry and before you know it you're caught in that dream. From the day I met her, I was captivated by her enthusiasm and knowledge about this topic. In fact, meeting Laura made me decide to join the university as I thought: if people like Laura work at THUAS, I want to be a part of this organization'. Over the years I have seen her finish the Msc in biomimicry at Arizona State University followed by a PhD at TUDelft. And all that next to her full time job as a teacher. It's only a miracle that she still found the time to go outdoors and be in Nature. But luckily, she did as this is what nourishes her - and that nourishment is brought into the classroom affecting generations of students. I am very proud of how she builds her tribe just like Nature does; grassroots from the bottom up, not supported but also not inhibited by formal structures. In that way she truly acts as a bridge helping others to tap into Nature's wisdom. This morning I harvested the remaining vegetables from my garden and turned them into lunch. It's the second year I grow vegetables and it feels like I am only at the beginning of learning to collaborate with Nature. In Spring and Summer, Ihave witnessed in awe how seeds become seedlings which then grow into mature plants carrying fruit. The sheer wonder of Nature never ceases to amaze me, and my garden is only an attempt to be more aware of seasonal rhythms. It's Autumn right now, a time of year that invites us to go inside, reflect and let go of old baggage that no longer serves us. We'll be approaching the stage of wintering soon in which our inner journey will benefit from the darkness of wintertime introspection, along with the space to process the old, integrate learnings, and then germinate the new. Over the course of her career, Laura has gone through these seasonal cycles - reinventing herself in the past decade as a teacher, researcher and regenerative leader. One of Laura's many qualities is that she embodies three leadership characteristics derived from Nature. First, she acknowledges the importance of interconnection. Many times, we think of Nature as being separate from us, but in reality we humans are Nature. Connection with Nature enables us to think within systems and understand that we can't direct the system, but instead we're all part of multiple systems. Second, sensing the system and our part in it builds resilience. Even if things don't go as we expected or imagined, rather than reacting, we can step back and engage with more insight. Laura's adaptability to a system's needs while spotting opportunities to crack it open, is admirable. As the system is always in evolution, so is she - remarkably receptive to change even in the final stages of her career. Third, Laura creates space for people to develop and thrive, acting as multipliers of her vision and love for the natural world. In her leadership she embodies the ideal elder while being able to perceive the world through the eyes of a child - with continuous wonder for how life unfolds. This book is a bricolage of Laura's post-doc research conducted the past two years. In it you will find an array of fascinating reads and tools that help you deepen your practice as a biomimicry professional. The book is a community effort integrating tools Laura has co-created with her ecosystem as well as more in-depth readings written by some of the talents she has nourished over time. I wish for you to enjoy this careful curation of both practical as well as more conceptual contributions. May it inspire your own thriving in bringing Nature based wisdom to the core of our daily lives.
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Post-earthquake structural damage shows that wall collapse is one of the most common failure mechanisms in unreinforced masonry buildings. It is expected to be a critical issue also in Groningen, located in the northern part of the Netherlands, where human-induced seismicity has become an uprising problem in recent years. The majority of the existing buildings in that area are composed of unreinforced masonry; they were not designed to withstand earthquakes since the area has never been affected by tectonic earthquakes. They are characterised by vulnerable structural elements such as slender walls, large openings and cavity walls. Hence, the assessment of unreinforced masonry buildings in the Groningen province has become of high relevance. The abovementioned issue motivates engineering companies in the region to research seismic assessments of the existing structures. One of the biggest challenges is to be able to monitor structures during events in order to provide a quick post-earthquake assessment hence to obtain progressive damage on structures. The research published in the literature shows that crack detection can be a very powerful tool as an assessment technique. In order to ensure an adequate measurement, state-of-art technologies can be used for crack detection, such as special sensors or deep learning techniques for pixel-level crack segmentation on masonry surfaces. In this project, a new experiment will be run on an in-plane test setup to systematically propagate cracks to be able to detect cracks by new crack detection tools, namely digital crack sensor and vision-based crack detection.
Criminologists have frequently debated whether offenders are specialists, in that they consistently perform either one offense or similar offenses, or versatile by performing any crime based on opportunities and situational provocations. Such foundational research has yet to be developed regarding cybercrimes, or offenses enabled by computer technology and the Internet. This study address this issue using a sample of 37 offender networks. The results show variations in the offending behaviors of those involved in cybercrime. Almost half of the offender networks in this sample appeared to be cybercrime specialists, in that they only performed certain forms of cybercrime. The other half performed various types of crimes on and offline. The relative equity in specialization relative to versatility, particularly in both on and offline activities, suggests that there may be limited value in treating cybercriminals as a distinct offender group. Furthermore, this study calls to question what factors influence an offender's pathway into cybercrime, whether as a specialized or versatile offender. The actors involved in cybercrime networks, whether as specialists or generalists, were enmeshed into broader online offender networks who may have helped recognize and act on opportunities to engage in phishing, malware, and other economic offenses.
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This literature review explores ways older workers might continue to make waves and impact their work organization. The topic of the paper is grounded in the problem of an ageing organizational population looming in the near future. The work presented here is a start to helping management in knowledge-intensive organizations to understand how to effectively utilize the capacities of older knowledge workers by stimulating intergenerational learning as a means to retain critical organizational knowledge, encourage innovation and promote organizational learning through knowledge building. First, the concept of intergenerational learning is developed followed by a discussion of the organizational factors important for it to take place. The last section presents ideas on how to design and implement intergenerational learning as an organizational development program.
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The Salvation Army has been battling social problems in the Netherlands for more than 125 years. Over the course of this period, the Dutch Salvation Army has developed into a well-known faith-based organization as well as an important professional social service provider. These two characteristics: religious work and social work, are regarded by the Army as essential to its identity, and are considered distinct but in – separable. However, as this study shows, during much of the Army’s history this bilateral character created an inescapable field of tension. This became explicitly clear with the development of the Dutch social policy system during the twentieth century, when the evolving relationship between the Salvation Army and the Dutch government created certain problems for both actors. How would the government cooperate with a valued social service provider that had an explicit faith-based identity? And on the other hand, how did the Army cope with this relationship in relation to its identity? The work presented in this thesis was supported by the University of Applied Sciences Utrecht (HU) and the VU University Amsterdam.
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