In recent years, the number of publications on innovation in the construction industry has increased. Many of these documents address qualitative issues, e.g. policies for innovation and present case studies. A more quantitative approach is taken in this paper, which is the continuation of a previous study. It focuses on main types and sources of innovation in the construction industry, and includes an analysis of 55 years of publications in two leading Dutch professional journals. The results show a recent increase in innovation, with two-thirds of innovations coming out of supplying industries. Construction companies contribute mainly in process innovations. Innovation in construction remains to be technology- rather than market-driven. Regulations have a surprising impact, as over one-third of all counted new innovations are related to new regulations.
In recent years, a step change has been seen in the rate of adoption of Industry 4.0 technologies by manufacturers and industrial organizations alike. This article discusses the current state of the art in the adoption of Industry 4.0 technologies within the construction industry. Increasing complexity in onsite construction projects coupled with the need for higher productivity is leading to increased interest in the potential use of Industry 4.0 technologies. This article discusses the relevance of the following key Industry 4.0 technologies to construction: data analytics and artificial intelligence, robotics and automation, building information management, sensors and wearables, digital twin, and industrial connectivity. Industrial connectivity is a key aspect as it ensures that all Industry 4.0 technologies are interconnected allowing the full benefits to be realized. This article also presents a research agenda for the adoption of Industry 4.0 technologies within the construction sector, a three-phase use of intelligent assets from the point of manufacture up to after build, and a four-staged R&D process for the implementation of smart wearables in a digital enhanced construction site.
The project aim is to improve collusion resistance of real-world content delivery systems. The research will address the following topics: • Dynamic tracing. Improve the Laarhoven et al. dynamic tracing constructions [1,2] [A11,A19]. Modify the tally based decoder [A1,A3] to make use of dynamic side information. • Defense against multi-channel attacks. Colluders can easily spread the usage of their content access keys over multiple channels, thus making tracing more difficult. These attack scenarios have hardly been studied. Our aim is to reach the same level of understanding as in the single-channel case, i.e. to know the location of the saddlepoint and to derive good accusation scores. Preferably we want to tackle multi-channel dynamic tracing. • Watermarking layer. The watermarking layer (how to embed secret information into content) and the coding layer (what symbols to embed) are mostly treated independently. By using soft decoding techniques and exploiting the “nuts and bolts” of the embedding technique as an extra engineering degree of freedom, one should be able to improve collusion resistance. • Machine Learning. Finding a score function against unknown attacks is difficult. For non-binary decisions there exists no optimal procedure like Neyman-Pearson scoring. We want to investigate if machine learning can yield a reliable way to classify users as attacker or innocent. • Attacker cost/benefit analysis. For the various use cases (static versus dynamic, single-channel versus multi-channel) we will devise economic models and use these to determine the range of operational parameters where the attackers have a financial benefit. For the first three topics we have a fairly accurate idea how they can be achieved, based on work done in the CREST project, which was headed by the main applicant. Neural Networks (NNs) have enjoyed great success in recognizing patterns, particularly Convolutional NNs in image recognition. Recurrent NNs ("LSTM networks") are successfully applied in translation tasks. We plan to combine these two approaches, inspired by traditional score functions, to study whether they can lead to improved tracing. An often-overlooked reality is that large-scale piracy runs as a for-profit business. Thus countermeasures need not be perfect, as long as they increase the attack cost enough to make piracy unattractive. In the field of collusion resistance, this cost analysis has never been performed yet; even a simple model will be valuable to understand which countermeasures are effective.
Individuals are increasingly confronted with ‘diseases of modernity’, such as stress and burnout. While insights from the work-family interface have mainly pointed towards demands and resources coming from the work and nonwork domains, the proposed multi-method PhD research project aims to contribute to contemporary scholarly and societal work-life and burnout debates by presenting an alternative theoretical lens on the development of mental health complaints in today’s society, especially among the younger Millennial generation. The project aims to shed light on how and why Millennial employees engage in a so-called ‘work/nonwork image (re)construction process’.The project will reflect on the following questions:How, why and when do individual workers engage in a process in which they construct their image(s) in the work and nonwork domains? What are the relationships, if any, between the image (re)construction process individuals engage in and potential positive- and negative consequences?The findings are expected to have important implications not only for preventive measures for individuals and organizations, but also for possible avenues for future studies. Project Partner: Nyenrode Business Universiteit
Structural Biology plays a crucial role in understanding the Chemistry of Life by providing detailed information about the three-dimensional structures of biological macromolecules such as proteins, DNA, RNA and complexes thereof. This knowledge allows researchers to understand how these molecules function and interact with each other, which forms the basis for a molecular understanding of disease and the development of targeted therapies. For decades, X-ray crystallography has been the dominant technique to determine these 3D structures. Only a decade ago, advances in technology and data processing resulted in a dramatic improvement of the resolution at which structures of biomolecular assemblies can be determined using another technique: cryo-electron microscopy (cryo-EM). This has been referred to as “the resolution revolution”. Since then, an ever increasing group of structural biologists are using cryo-EM. They employ a technique named Single Particle Analysis (SPA), in which thousands of individual macromolecules are imaged. These images are then computationally iteratively aligned and averaged to generate a three-dimensional reconstruction of the macromolecule. SPA works best if a very pure and concentrated macromolecule of interest can be captured in random orientations within a thin layer (10-50nm) of vitreous ice. Maastricht University has been the inventor of the machine that is found in most labs worldwide used for this: the VitroBot. We have been the inventor of succeeding technologies that allow for much better control of this process: the VitroJet. In here, we will develop a novel chemical way to expand our arsenal for preparing SPA samples of defined thickness. We will design, produce and test chemical spacers to allow for a controlled sample thickness. If successful, this will provide an easy, affordable solution for the ~1000 laboratories worldwide using SPA, and help them with their in vitro studies necessary for an improved molecular understanding of the Chemistry of Life.
