Electric vehicles and renewable energy sources are collectively being developed as a synergetic implementation for smart grids. In this context, smart charging of electric vehicles and vehicle-to-grid technologies are seen as a way forward to achieve economic, technical and environmental benefits. The implementation of these technologies requires the cooperation of the end-electricity user, the electric vehicle owner, the system operator and policy makers. These stakeholders pursue different and sometime conflicting objectives. In this paper, the concept of multi-objective-techno-economic-environmental optimisation is proposed for scheduling electric vehicle charging/discharging. End user energy cost, battery degradation, grid interaction and CO2 emissions in the home micro-grid context are modelled and concurrently optimised for the first time while providing frequency regulation. The results from three case studies show that the proposed method reduces the energy cost, battery degradation, CO2 emissions and grid utilisation by 88.2%, 67%, 34% and 90% respectively, when compared to uncontrolled electric vehicle charging. Furthermore, with multiple optimal solutions, in order to achieve a 41.8% improvement in grid utilisation, the system operator needs to compensate the end electricity user and the electric vehicle owner for their incurred benefit loss of 27.34% and 9.7% respectively, to stimulate participation in energy services.
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This article draws on Robinson, McNeill and Maruna’s argument (2012) about the adaptability of community sanctions and measures, observed through four distinctive penal narratives, in order to shed light on the regional development of community service in Wroclaw, Poland. While the managerial adaptation of community sanctions is underpinned by an inter-agency cooperation to fulfil the goals of the system, the contemporary rehabilitation iteration has become a toolkit of measures predominantly phrased around risk management, the reparative discourse seeks various means to repair harm, and the punitive orientation represent the turn to desert-based and populist sentencing frameworks. In this article, the first three are reflected upon along with the emerging, restorative adaptation of community sanctions. The last one is added to expand on the findings of previous research, which suggests the viability of the restorative orientation for community service in Poland (Matczak, 2018). A brief discussion of how punishment, probation and restorative justice can be reconciled is followed by the introduction of Polish Probation and the role of probation officers in delivering community service in Poland. Although the penal narratives are visible in the Wrocław model to different degrees and in various combinations, more research is required to evaluate the viability of a progressive orientation to punishment during a gradual optimisation of community orders. Originally published: Anna Matczak, The penal narratives of community sentence and the role of probation: The case of the Wrocław model of community service, European journal of probation (Vol. 13 nr. 1) pp. 72-88. Copyright © 2021year (The Author). DOI: 10.1177/2066220320976105
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Binnen het projectonderwijs wordt nog vaak drooggezwommen. Enerzijds door de verstrekte projectopdrachten anderzijds door de suboptimalisatie van oplossingen. Deze zijn namelijk sterk afhankelijk van de verbonden modules en docenten. In de praktijk zijn de oplossingen echter altijd een afweging van tijd, geld en kwaliteit. Onze Human Engineers leren om daar op een goede manier mee om te gaan. Dit door de integratiemodule Integrated Product Development (IPD). IPD is een multidisciplinair project waarbij studenten van verschillende Fontys Instituten werken aan de commercikle en technische uitwerking van een bedrijfsopdracht. Marktonderzoek, doelgroep bepaling en productspecificatie zijn een vast onderdeel van een IPD project evenals het ontwerpen en bouwen van een prototype en het financieel onderbouwen van een Go/NO go advies aan de ondernemer. Het project vindt plaats in het laatste onderwijssemester, net vssr het afstuderen en is dus te zien als een open project met een bedrijf als opdrachtgever. De Human Engineering studenten zijn in deze projecten de verbindende schakel. De specialisten in de projectgroepen, de technische studenten, willen nogal eens zoeken naar mooie oplossingen vooral in technische zin. Daarbij gaan ze vaak volledig voorbij aan het belang van de ondernemer (winst maken) en het belang van de klant (kwaliteit en bedieningsgemak). Ook het projectwerk heeft een enorme sprong vooruit gemaakt door het team uit te breiden met Human Engineers. De Human Engineering studenten focussen vooral ook op het halen van targets (kosten) en deadlines (tijd), het maken en nakomen van afspraken en de communicatie binnen de groep en naar buiten toe (ondernemer en klant). Huidige studenten en alumni geven aan dat het project zeer realistisch is en dat het vergelijkbaar is met problemen die ze in hun werk tegen komen. Zeker blijven doen is hun advies. Organisatorisch vergt het wel een en ander omdat er bijvoorbeeld afstemming dient te komen tussen de verschillende instituten met betrekking tot: beoordeling van de studenten, afstemmen van lesroosters en vergoeding voor docenten. Ook het onderhouden van bedrijfsrelaties om bijvoorbeeld aan de opdrachten te komen blijft een moeilijke, tijdrovende zaak.
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The full potential of predictive maintenance has not yet been utilised. Current solutions focus on individual steps of the predictive maintenance cycle and only work for very specific settings. The overarching challenge of predictive maintenance is to leverage these individual building blocks to obtain a framework that supports optimal maintenance and asset management. The PrimaVera project has identified four obstacles to tackle in order to utilise predictive maintenance at its full potential: lack of orchestration and automation of the predictive maintenance workflow, inaccurate or incomplete data and the role of human and organisational factors in data-driven decision support tools. Furthermore, an intuitive generic applicable predictive maintenance process model is presented in this paper to provide a structured way of deploying predictive maintenance solutions https://doi.org/10.3390/app10238348 LinkedIn: https://www.linkedin.com/in/john-bolte-0856134/
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Adaptive survey design has attracted great interest in recent years, but the number of case studies describing actual implementation is still thin. Reasons for this may be the gap between survey methodology and data collection, practical complications in differentiating effort across sample units and lack of flexibility of survey case management systems. Currently, adaptive survey design is a standard option in redesigns of person and household surveys at Statistics Netherlands and it has been implemented for the Dutch Health survey in 2018. In this article, the implementation of static adaptive survey designs is described and motivated with a focus on practical feasibility.
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The percentage of sports and leisure shoes sold worldwide is gradually increasing. However, consumers have little or no objective information on the mechanical properties of the shoes. A justified selection protocol of sports and leisure shoes based on static and dynamic shoe properties considering the intended use is essential. Today, commonly accepted dynamic test protocols for (sports) shoes do not exist. The development of an artificial parametric foot as part of an innovative robot gait simulator is a tool to objectify shoe properties independently from possible compensations encountered during assessment of test persons. This contribution discusses the development of an artificial foot enabling objective testing of the mechanical and functional properties of sports and leisure shoes.
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Background: Due to the increasing number of older people with multi-morbidity, the demand for outpatient geriatric rehabilitation (OGR) will also increase. Objective: To assess the effects of OGR on the primary outcome functional performance (FP) and secondary outcomes: length of in-patient stay, re-admission rate, patients’ and caregivers’ quality of life, mortality and cost-effectiveness. We also aim to describe the organisation and content of OGR. Methods: Systematic review and meta-analysis. Five databases were queried from inception to July 2022. We selected randomised controlled trials written in English, focusing on multidisciplinary interventions related to OGR, included participants aged ≥65 and reported one of the main outcomes. A meta-analysis was performed on FP, patients’ quality of life, length of stay and re-admissions. The structural, procedural and environmental aspects of OGR were systematically mapped. Results: We selected 24 studies involving 3,405 participants. The meta-analysis showed no significant effect on the primary outcome FP (activity). It demonstrated a significant effect of OGR on shortening length of in-patient stay (P = 0.03, MD = −2.41 days, 95%CI: [−4.61—0.22]). Frequently used elements of OGR are: inpatient start of OGR with an interdisciplinary rehabilitation team, close cooperation with primary care, an OGR coordinator, individual goal setting and education for both patient and caregiver. Conclusion: This review showed that OGR is as effective as usual care on FP activity. It shows low certainty of evidence for OGR being effective in reducing the length of inpatient stay. Further research is needed on the various frequently used elements of OGR
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Background Running-related injuries (RRIs) can be considered the primary enemy of runners. Most literature on injury prediction and prevention overlooks the mental aspects of overtraining and under-recovery, despite their potential role in injury prediction and prevention. Consequently, knowledge on the role of mental aspects in RRIs is lacking. Objective To investigate mental aspects of overtraining and under-recovery by means of an online injury prevention programme. Methods and analysis The ‘Take a Mental Break!’ study is a randomised controlled trial with a 12 month follow-up. After completing a web-based baseline survey, half and full marathon runners were randomly assigned to the intervention group or the control group. Participants of the intervention group obtained access to an online injury prevention programme, consisting of a running-related smartphone application. This app provided the participants of the intervention group with information on how to prevent overtraining and RRIs with special attention to mental aspects. The primary outcome measure is any self-reported RRI over the past 12 months. Secondary outcome measures include vigour, fatigue, sleep and perceived running performance. Regression analysis will be conducted to investigate whether the injury prevention programme has led to a lower prevalence of RRIs, better health and improved perceived running performance. Ethics and dissemination The Medical Ethics Committee of the University Medical Center Utrecht, the Netherlands, has exempted the current study from ethical approval (reference number: NL64342.041.17). Results of the study will be communicated through scientific articles in peer-reviewed journals, scientific reports and presentations on scientific conferences.
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Key to reinforcement learning in multi-agent systems is the ability to exploit the fact that agents only directly influence only a small subset of the other agents. Such loose couplings are often modelled using a graphical model: a coordination graph. Finding an (approximately) optimal joint action for a given coordination graph is therefore a central subroutine in cooperative multi-agent reinforcement learning (MARL). Much research in MARL focuses on how to gradually update the parameters of the coordination graph, whilst leaving the solving of the coordination graph up to a known typically exact and generic subroutine. However, exact methods { e.g., Variable Elimination { do not scale well, and generic methods do not exploit the MARL setting of gradually updating a coordination graph and recomputing the joint action to select. In this paper, we examine what happens if we use a heuristic method, i.e., local search, to select joint actions in MARL, and whether we can use outcome of this local search from a previous time-step to speed up and improve local search. We show empirically that by using local search, we can scale up to many agents and complex coordination graphs, and that by reusing joint actions from the previous time-step to initialise local search, we can both improve the quality of the joint actions found and the speed with which these joint actions are found.
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Companies in the Brainport region are often characterized as high mix low volume (HMLV) production environments. These companies are distinguished by a wide range of possible products (high product variety), which are produced in low volumes. These are often customer-specific products that are produced once or incidentally. Traditionally, these companies focus on efficient use of resources, where utilisation rate and cost coverage are relevant. The increasing customer demand in the region leads to pressure on production capacity. An initial intuitive response from these companies is to further increase the utilisation rate of machines. To keep costs manageable, the company tries to avoid investing in additional capacity. An undesirable side effect is increasing pressure on timeliness (delivery, such as lead times, delivery reliability, flexibility) and quality. The apparent contradiction between costs and timeliness in these HMLV production environments is a recurring issue in practice-oriented research conducted by Fontys Industrial Engineering and Management students. This results in the following research question: Which sub-aspects may be relevant to the performance regarding Quality, Delivery, and Cost (QDC) of an HMLV production environment?
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