From the article: Abstract. This exploratory and conceptual article sets out to research what arguments and possibilities for experimentation in construction exists and if experimentation can contribute towards more innovative construction as a whole. Traditional, -western- construction is very conservative and regional, often following a traditional and linear design process, which focuses on front-loaded cost savings and repetitive efficiency, rather than securing market position through innovation. Thus becoming a hindrance for the development of the sector as a whole. Exploring the effects of using the, in other design-sectors commonly and successfully practiced, “four-phased iterative method” in architectural construction could be the start of transforming the conservative construction industry towards a more innovative construction industry. The goal of this research is to find whether the proposed strategy would indeed result in a higher learning curve and more innovation during the - architectural- process. Preliminary research indicates that there is argumentation for a more experimental approach to construction.
Ship-source greenhouse gas (GHG) emissions could increase by up to 250% from 2012 levels by 2050 owing to increasing global freight volumes. Binding international legal agreements to regulate GHGs, however, are lacking as technical solutions remain expensive and crucial industrial support is absent. In 2003, IMO adopted Resolution A.963 (23) to regulate shipping CO2 emissions via technical, operational, and market-based routes. However, progress has been slow and uncertain; there is no concrete emission reduction target or definitive action plan. Yet, a full-fledged roadmap may not even emerge until 2023. In this policy analysis, we revisit the progress of technical, operational, and market-based routes and the associated controversies. We argue that 1) a performance-based index, though good-intentioned, has loopholes affecting meaningful CO2 emission reductions driven by technical advancements; 2) using slow steaming to cut energy consumption stands out among operational solutions thanks to its immediate and obvious results, but with the already slow speed in practice, this single source has limited emission reduction potential; 3) without a technology-savvy shipping industry, a market-based approach is essentially needed to address the environmental impact. To give shipping a 50:50 chance for contributing fairly and proportionately to keep global warming below 2°C, deep emission reductions should occur soon.
Abstract: Background: There has been a rapid increase in the population of senior citizens in many countries. The shortage of caregivers is becoming a pressing concern. Robots are being deployed in an attempt to fill this gap and reduce the workload of caregivers. This study explores how healthcare robots are perceived by trainee care professionals. Methods: A total of 2365 students at different vocational levels completed a questionnaire, rating ethical statements regarding beneficence, maleficence, justice, autonomy, utility, and use intentions with regard to three different types of robots (assistive, monitoring, and companion) along with six control variables: gender, age, school year, technical skills, interest in technology, and enjoying working with computers.
Traffic accidents are a severe public health problem worldwide, accounting for approximately 1.35 million deaths annually. Besides the loss of life, the social costs (accidents, congestion, and environmental damage) are significant. In the Netherlands, in 2018, these social costs were approximately € 28 billion, in which traffic accidents alone accounted for € 17 billion. Experts believe that Automated Driving Systems (ADS) can significantly reduce these traffic fatalities and injuries. For this reason, the European Union mandates several ADS in new vehicles from 2022 onwards. However, the utility of ADS still proves to present difficulties, and their acceptance among drivers is generally low. As of now, ADS only supports drivers within their pre-defined safety and comfort margins without considering individual drivers’ preferences, limiting ADS in behaving and interacting naturally with drivers and other road users. Thereby, drivers are susceptible to distraction (when out-of-the-loop), cannot monitor the traffic environment nor supervise the ADS adequately. These aspects induce the gap between drivers and ADS, raising doubts about ADS’ usefulness among drivers and, subsequently, affecting ADS acceptance and usage by drivers. To resolve this issue, the HUBRIS Phase-2 consortium of expert academic and industry partners aims at developing a self-learning high-level control system, namely, Human Counterpart, to bridge the gap between drivers and ADS. The central research question of this research is: How to develop and demonstrate a human counterpart system that can enable socially responsible human-like behaviour for automated driving systems? HUBRIS Phase-2 will result in the development of the human counterpart system to improve the trust and acceptance of drivers regarding ADS. In this RAAK-PRO project, the development of this system is validated in two use-cases: I. Highway: non-professional drivers; II. Distribution Centre: professional drivers.
Traffic accidents are a severe public health problem worldwide, accounting for approximately 1.35 million deaths annually. Besides the loss of life, the social costs (accidents, congestion, and environmental damage) are significant. In the Netherlands, in 2018, these social costs were approximately € 28 billion, in which traffic accidents alone accounted for € 17 billion. Experts believe that Automated Driving Systems (ADS) can significantly reduce these traffic fatalities and injuries. For this reason, the European Union mandates several ADS in new vehicles from 2022 onwards. However, the utility of ADS still proves to present difficulties, and their acceptance among drivers is generally low.As of now, ADS only supports drivers within their pre-defined safety and comfort margins without considering individual drivers’ preferences, limiting ADS in behaving and interacting naturally with drivers and other road users. Thereby, drivers are susceptible to distraction (when out-of-the-loop), cannot monitor the traffic environment nor supervise the ADS adequately. These aspects induce the gap between drivers and ADS, raising doubts about ADS’ usefulness among drivers and, subsequently, affecting ADS acceptance and usage by drivers.To resolve this issue, the HUBRIS Phase-2 consortium of expert academic and industry partners aims at developing a self-learning high-level control system, namely, Human Counterpart, to bridge the gap between drivers and ADS. The central research question of this research is:How to develop and demonstrate a human counterpart system that can enable socially responsible human-like behaviour for automated driving systems?HUBRIS Phase-2 will result in the development of the human counterpart system to improve the trust and acceptance of drivers regarding ADS. In this RAAK-PRO project, the development of this system is validated in two use-cases:I. Highway: non-professional drivers;II. Distribution Centre: professional drivers.Collaborative partners:Bielefeld University of Applied Sciences, Bricklog B.V., Goudappel B.V., HaskoningDHV Nederland B.V., Rhine-Waal University of Applied Sciences, Rijkswaterstaat, Saxion, Sencure B.V., Siemens Industry Software Netherlands B.V., Smits Opleidingen B.V., Stichting Innovatiecentrum Verkeer en Logistiek, TNO Den Haag, TU Delft, University of Twente, V-Tron B.V., XL Businesspark Twente.
The postdoc candidate, Sondos Saad, will strengthen connections between research groups Asset Management(AM), Data Science(DS) and Civil Engineering bachelor programme(CE) of HZ. The proposed research aims at deepening the knowledge about the complex multidisciplinary performance deterioration prediction of turbomachinery to optimize cleaning costs, decrease failure risk and promote the efficient use of water &energy resources. It targets the key challenges faced by industries, oil &gas refineries, utility companies in the adoption of circular maintenance. The study of AM is already part of CE curriculum, but the ambition of this postdoc is that also AM principles are applied and visible. Therefore, from the first year of the programme, the postdoc will develop an AM material science line and will facilitate applied research experiences for students, in collaboration with engineering companies, operation &maintenance contractors and governmental bodies. Consequently, a new generation of efficient sustainability sensitive civil engineers could be trained, as the labour market requires. The subject is broad and relevant for the future of our built environment being more sustainable with less CO2 footprint, with possible connections with other fields of study, such as Engineering, Economics &Chemistry. The project is also strongly contributing to the goals of the National Science Agenda(NWA), in themes of “Circulaire economie en grondstoffenefficiëntie”,”Meten en detecteren: altijd, alles en overall” &”Smart Industry”. The final products will be a framework for data-driven AM to determine and quantify key parameters of degradation in performance for predictive AM strategies, for the application as a diagnostic decision-support toolbox for optimizing cleaning &maintenance; a portfolio of applications &examples; and a new continuous learning line about AM within CE curriculum. The postdoc will be mentored and supervised by the Lector of AM research group and by the study programme coordinator(SPC). The personnel policy and job function series of HZ facilitates the development opportunity.
