Public Procurement of Innovation Through Increased Startup Participation: The Case of Digipolis (Research-in-progress)

Previous research has identified numerous obstacles that hinder the efficient procurement of innovation by the public sector. This paper introduces the case of Digipolis - the public ICT service provider of the City of Antwerp in Belgium. In 2015, the company implemented a comprehensive overhaul of its procurement strategy centered around 3 key components: a flexible procurement process, a community built around Digital Antwerp, and a challenge-oriented company culture. The case adopts a holistic perspective on the implementation of innovation procurement in a local public sector organization, and investigates the specific conditions and mechanisms that allowed to leverage the Antwerp startup community in order to increase the number of purchased innovative solutions. The case also sheds light on how public procurement of innovation can lead to knowledge-intensive entrepreneurship - an area that is still largely undiscovered

Design optimisation for optically tracked pointers

The use of mechanical pointers in optical tracking systems is needed to aid registration processes of unlocated rigid bodies. Error on the target point of a pointer can cause wrong positioning of vital objects and as such these errors have to be avoided. In this paper, the different errors that originate during this process are described, after which this error analysis is used for the optimisation of an improved pointer design. The final design contains six coplanar fiducials, favored by its robustness and low error. This configuration of fiducials is then analysed theoretically as well as practically to understand how it is performing. The error on tracking the target point of the pointer is found with simulation to be around 0.7 times the error of measuring one fiducial in space. However, practically this error is about equal to the fiducial tracking error, due to the non-normally distributed errors on each separate fiducial

Naar een open innovatiemodel in Vlaamse steden en gemeenten

Steden en gemeenten staan voor belangrijke uitdagingen. Ondanks budgettaire restricties, wordt in toenemende mate verwacht dat de publieke sector digitaal leiderschap neemt. Digitalisering wordt beschouwd als een belangrijk instrument voor een slimme overheid met een publieke dienstverlening die offline en online elementen naadloos integreert. Nieuwe digitale technologieën, zoals blockchain of artificiële intelligentie, bieden bovendien belangrijke opportuniteiten om de efficiëntie en responsiviteit van de overheid te verbeteren. Het uitbouwen van een digitaal getransformeerde overheid, die ook inzet op andere maatschappelijke thema’s zoals duurzaamheid, is een heuse uitdaging. “No matter who you are, most of the smartest people work for someone else.” –Bill Joy (Wet van Joy) Open innovatie kan een belangrijke katalysator zijn om de opportuniteiten van zulke transformaties in de overheid te verzilveren. Open innovatie start vanuit de erkenning dat innovatieve kennis wijdverspreid is in de samenleving, en verwijst naar het openen van de interne innovatieprocessen naar externe kennisbronnen. Door zich strategisch te positioneren in een innovatie-ecosysteem kan de overheid gebruik maken van kennis die buiten de organisatiegrenzen aanwezig is om haar maatschappelijke rol beter te volbrengen. Open innoveren verschuift de rol van overheden van probleemoplosser naar oplossingszoeker – eerder dan problemen te lijf te gaan met enkel de interne middelen, wordt een oplossing gezocht door gebruik te maken van innovatieve kennis die intern én extern aanwezig is. Het aanboren van zulke externe kennis omvat veelal een brede groep innovatieve actoren die in het verleden niet of weinig in contact kwamen met overheidsorganisaties, zoals startups, KMOs/MKBs, niet-gouvernementele organisaties en burgers. KEY TAKEAWAY: Belangrijke uitdagingen voor steden en gemeenten kunnen best worden aangegaan door externe innovatieve actoren te betrekken. Een ecosysteem-visie op innovatie laat toe om zowel interne als externe kennis in te zetten

Towards Parallel Large-Scale Genomic Prediction by Coupling Sparse and Dense Matrix Algebra

Genomic prediction for plant breeding requires taking into account environmental effects and variations of genetic effects across environments. The latter can be modelled by estimating the effect of each genetic marker in every possible environmental condition, which leads to a huge amount of effects to be estimated. Nonetheless, the information about these effects is only sparsely present, due to the fact that plants are only tested in a limited number of environmental conditions. In contrast, the genotypes of the plants are a dense source of information and thus the estimation of both types of effects in one single step would require as well dense as sparse matrix formalisms. This paper presents a way to efficiently apply a high performance computing infrastructure for dealing with large-scale genomic prediction settings, relying on the coupling of dense and sparse matrix algebra

Embry-Riddle Fly Paper 1943-01-15

https://commons.erau.edu/fly-paper/1159/thumbnail.jp

Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).

Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and ≥1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (n = 5069) or prospectively (n = 5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (≤6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; p = 0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)