By use of a literature review and an environmental scan four plausible future scenarios will be created, based on the research question: How could the future of backpack tourism look like in 2030, and how could tourism businesses anticipate on the changing demand. The scenarios, which allow one to ‘think out of the box’, will eventually be translated into recommendations towards the tourism sector and therefore can create a future proof company strategy.
In the project the students were asked to design a material bank to facilitate a circular construction industry. The insights they gained were used to create opportunities to renovate the road ' 'Griffiersveld” circularly. This research report was written by three students involved in the course "Industrial and sustainable building" of Saxion University of Applied Sciences.
This deliverable focuses on the construction industry of the Netherlands.The construction industry has a reputation for being inefficient. Innovation in construction logistics is needed to ensure that cities stay liveable. To create innovation in constructionlogistics, collaboration between stakeholders is necessary. However, the lack of reliable quantitative data is a problem. Reliable quantitative data are necessary to convince stakeholders for new collaborations that are needed for innovations in construction logistics. There is, therefore, a need to examine the current state of construction logistics calculation models. The integrated logistics concept (ILC) is used to examine construction logistics processes and to address factors that obstruct the development of construction logistics calculation models.
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.
Climate change has impacted our planet ecosystem(s) in many ways. Among other alterations, the predominance of long(er) drought periods became a point of concern for many countries. A good example is The Netherlands, a country known by its channels and abundant surface water, which has listed “drought effect mitigation” among the different topics in the last version of its “Innovation Agenda” (Kennis en Innovatie Agenda, KIA). There are many challenges to tackle in such scenario, one of them is solutions for small/decentralized communities that suffer from dry-up of surface reservoirs and have no groundwater source available. Such sites are normally far from big cities and coastal zones, which impair the supply via distribution networks. In such cases, Atmospheric Water Generation (AWG) technologies are a plausible solution. These systems have relatively small production rates (few m3 per day), but they can still provide enough volume for cities with up to 100k inhabitants. Despite having real scale systems already installed in different locations worldwide, most systems are between TRL 5 and 6. Thus need further development. SunCET proposes an in-situ evaluation of an AWG system (WaterWin) developed by two different Dutch companies (Solaq and Sustainable Eyes) in the Brazilian semi-arid state of Ceará. The cooperation with NHL Stenden will provide the necessary expertise, analytical and technical support to conduct the tests. The state government of Ceará built an infrastructure to support the realization of in-situ tests, as they want to further accelerate technology implementation in the state. Such structure will make it possible to share costs and decrease total investments for the SMEs. Finally, it is also intended to help establishing partnerships between Dutch SMEs and Brazilian end users, i.e. municipalities of the Ceará state and small agriculture companies in the region.
