The Internet introduces new business choices for customer interaction. In this article we introduce two claims. Firstly, we will show that the way companies shape their customer interaction, and not their sector or size, determine the market segmentation. Secondly, Internet dynamics and its effect on customer interaction rebalances the companies’ marketing and sales function: the Internet shortens the time window for new market opportunities and makes everyone a salesman. Therefore, traditional marketing activities become more and more part of Sales. Corporate communication and branding become more vital.
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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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aving access to accurate and recent digital twins of infrastructure assets benefits the renovation, maintenance, condition monitoring, and construction planning of infrastructural projects. There are many cases where such a digital twin does not yet exist, such as for legacy structures. In order to create such a digital twin, a mobile laser scanner can be used to capture the geometric representation of the structure. With the aid of semantic segmentation, the scene can be decomposed into different object classes. This decomposition can then be used to retrieve cad models from a cad library to create an accurate digital twin. This study explores three deep-learning-based models for semantic segmentation of point clouds in a practical real-world setting: PointNet++, SuperPoint Graph, and Point Transformer. This study focuses on the use case of catenary arches of the Dutch railway system in collaboration with Strukton Rail, a major contractor for rail projects. A challenging, varied, high-resolution, and annotated dataset for evaluating point cloud segmentation models in railway settings is presented. The dataset contains 14 individually labelled classes and is the first of its kind to be made publicly available. A modified PointNet++ model achieved the best mean class Intersection over Union (IoU) of 71% for the semantic segmentation task on this new, diverse, and challenging dataset.
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Creating and testing the first Brand Segmentation Model in Augmented Reality using Microsoft Hololens. Sanoma together with SAMR launched an online brand segmentation tool based on large scale research, The brand model uses several brand values divided over three axes. However they cannot be displayed clearly in a 2D model. The space of BSR Quality Planner can be seen as a 3-dimensional meaningful space that is defined by the terms used to typify the brands. The third axis concerns a behaviour-based dimension: from ‘quirky behaviour’ to ‘standardadjusted behaviour’ (respectful, tolerant, solidarity). ‘Virtual/augmented reality’ does make it possible to clearly display (and experience) 3D. The Academy for Digital Entertainment (ADE) of Breda University of Applied Sciences has created the BSR Quality Planner in Virtual Reality – as a hologram. It’s the world’s first segmentation model in AR. Breda University of Applied Sciences (professorship Digital Media Concepts) has deployed hologram technology in order to use and demonstrate the planning tool in 3D. The Microsoft HoloLens can be used to experience the model in 3D while the user still sees the actual surroundings (unlike VR, with AR the space in which the user is active remains visible). The HoloLens is wireless, so the user can easily walk around the hologram. The device is operated using finger gestures, eye movements or voice commands. On a computer screen, other people who are present can watch along with the user. Research showed the added value of the AR model.Partners:Sanoma MediaMarketResponse (SAMR)
The project focuses on sustainable travel attitude and behaviour with attention to balance, liveability, impact and climate change (as indicated above). The customer journey is approached from the consumer side and intends to shed light on the way COVID-19 has influenced (or not) the following aspects:• consumer’s understanding and appreciation of sustainability • the extent to which this understanding has influenced their attitude towards sustainable travel choices• the extent to which this change is represented in their actual and projected travel behaviour throughout the travel decision-making process • conditions that may foster a more sustainable travel behaviourThe project can be seen as a follow up to existing studies on travel intention during and post COVID-19, such as ETC’s publication on Monitoring sentiment for domestic and Intra-European travel – Wave 5, or the joint study of the European Tourism Futures Institute (ETFI – www.etfi.nl) and the Centre of Expertise in Leisure, Tourism and Hospitality (CELTH – www.celth.nl) highlighting four future scenarios for the leisure, tourism and hospitality sectors post COVID-19. The project will look beyond travel intention and will supplement existing knowledge with crucial information on the way consumers view sustainability and the extent to which they are willing to adjust their travel behaviour to aid the recovery of a more sustainable travel and tourism industry. Therefore, the report aims to generate knowledge vital for the understanding of consumer trends and the role sustainability will play in travel choices in the near future.Problem statementPlease describe which question in the (participating) industry is addressed.How has the sustainable travel attitude and behaviour in selected European source markets been influenced by the COVID-19 pandemic? Further questions to be answered:• How did the COVID-19 pandemic influence the consumer’s understanding and appreciation of sustainability?• To what extent did this understanding influence their attitude towards sustainable travel choices?• To what extent is this change represented in their actual and projected travel behaviour throughout the travel decision-making process?• What are the conditions that may foster a more sustainable travel behaviour?
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. The validated product of the experiment will be tested on the monument of Fraeylemaborg.
