AGM-Style Revision of Beliefs and Intentions from a Database Perspective (Preliminary Version)

We introduce a logic for temporal beliefs and intentions based on Shoham's database perspective. We separate strong beliefs from weak beliefs. Strong beliefs are independent from intentions, while weak beliefs are obtained by adding intentions to strong beliefs and everything that follows from that. We formalize coherence conditions on strong beliefs and intentions. We provide AGM-style postulates for the revision of strong beliefs and intentions. We show in a representation theorem that a revision operator satisfying our postulates can be represented by a pre-order on interpretations of the beliefs, together with a selection function for the intentions

Insights from a Study on Decision Making in Enterprise Architecture

Abstract. Although there are many frameworks for Enterprise Architecture (EA), they focus mainly on the holistic structure of an enterprise and rarely take decision making into account. This is surprising, given the large role that (design) decision making seems to play in EA. A lack of empirical work offering insight into decision making in practice might be the cause of this. To address this knowledge gap we report on some first insights from an empirical study on how the practice of decision making in EA is perceived by professional enterprise architects. We sketch an outline of designing and decision making in contemporary EA, including a high level of politicization, emotional decision making, and subordination to business management. We discuss the implications of these findings for further research and work centered around EA

Argumentation-based Methodology for Goal-oriented Requirements Language (GRL)

Goal-oriented Requirements Language (GRL) aims to capture goals and non-functional requirements of stakeholders and analyzing alternative solutions for realizing these goals. GRL also documents the rationale behind selecting certain goals or alternatives. However, it does not have any means to document and trace back all of the arguments that occur during the stakeholder’s discussion process. To address this, we have developed the RationalGRL framework. RationalGRL combines techniques for formal argumentation from artificial intelligence with goal modeling in GRL. However, we did not specify how practitioners can actually use this framework. In this paper we discuss the methodology for RationalGRL, which consists of two processes, goal modeling and argumentation, that can be done interchangeably. We motivate our approach with an example

RationalGRL: A Framework for Argumentation and Goal Modeling

Goal-oriented requirements modeling approaches aim to capture the intentions of the stakeholders involved in the development of an information system as goals and tasks. The process of constructing such goal models usually involves discussions between a requirements engineer and a group of stakeholders. Not all the arguments in such discussions can be captured as goals or tasks: e.g., the discussion whether to accept or reject a certain goal and the rationale for acceptance or rejection cannot be captured in goal models. In this paper, we apply techniques from computational argumentation to a goal modeling approach by using a coding analysis in which stakeholders discuss requirements for a Traffic Simulator. We combine a simplified version of a traditional goal model, the Goal-oriented Requirements Language (GRL), with ideas from argumentation on schemes for practical reasoning into a new framework (RationalGRL). RationalGRL provides a formal semantics and tool support to capture the discussions and outcomes of the argumentation process that leads to a goal model. We also define the RationalGRL development process to create a RationalGRL model

Assessing the Carbon Footprint of Telemedicine:A Systematic Review

Background: Healthcare is responsible for 4% to 10% of carbon emissions worldwide, of which 22% is related to transport. Telemedicine emerged as a potential solution to reduce the footprint, for example, by reducing travel. However, a need to understand which variables to include in carbon footprint estimations in telemedicine limits our understanding of the beneficial impact telemedicine might have on our environment. This paper aims to systematically assess the reported carbon footprint and include variables assessed by the literature, comparing telemedicine with usual care. Methods: The systematic review followed the PRISMA guidelines in PubMed, Medline, Embase and Scopus. A quality assessment was performed using a transparency checklist for carbon footprint calculators. Carbon emissions were evaluated based on four categories, including patient travel, and streamlined life cycle assessment (LCA) for assessing included variables relevant to telemedicine. Results: We included 33 articles from 1117 records for analysis. The average transparency score was 38% (range 18%-68%). The median roundtrip travel distance for each patient was 131 km (interquartile range [IQR]: 60.8-351), or 25.6 kgCO2 (IQR: 10.6-105.6) emissions. There is high variance among included variables. Saved emissions are structurally underestimated by not including external factors such as a streamlined LCA.Conclusions: Telemedicine aids in reducing emissions, with travel distance being the most significant contributor. Additionally, we recommend accounting for the LCA since it highlights important nuances. This review furthers the debate on assessing carbon footprint savings due to telemedicine.</p

Cost-effectiveness of Direct Transfer to Angiography Suite of Patients With Suspected Large Vessel Occlusion

Cost-effectiveness; Angiography; Large vessel occlusionCost-efectivitat; Angiografia; Oclusió de grans vasosCosto-efectividad; Angiografía; Oclusión de grandes vasosBackground and Objectives Patients with acute ischemic stroke due to large vessel occlusion (LVO) deemed eligible for endovascular thrombectomy (EVT) are transferred from the emergency room to the angiography suite to undergo the procedure. Recently, the strategy of direct transfer of patients with suspected LVO to the angiography suite (DTAS) has been shown to improve functional outcomes. This study aims to evaluate the cost-effectiveness of the DTAS strategy vs initial transfer of patients with suspected LVO (Rapid Arterial Occlusion Evaluation score >4 and NIH Stroke Scale >10) to the emergency room (ITER). Methods A decision-analytic Markov model was developed to estimate the cost-effectiveness of the DTAS strategy vs the ITER strategy from a Dutch health care perspective with a 10-year time horizon. The primary outcome was the incremental cost-effectiveness ratio (ICER) using Dutch thresholds of $59,135 (€50,000) and$94,616 (€80,000) per quality-adjusted life year (QALY). Uncertainty of input parameters was assessed using 1-way sensitivity analysis, scenario analysis, and probabilistic sensitivity analysis. Results The DTAS strategy yielded 0.65 additional QALYs at an additional $16,089, resulting in an ICER of$24,925/QALY compared with the ITER strategy. The ICER varied from $27,169 to$38,325/QALY across different scenarios. The probabilistic sensitivity analysis showed that the DTAS strategy had a 91.8% and 97.0% likelihood of being cost-effective at a decision threshold of $59,135/QALY and$94,616/QALY, respectively. Discussion The cost-effectiveness of the DTAS strategy over ITER is robust for patients with suspected LVO. Together with recently published clinical results, this means that implementation of the DTAS strategy may be considered to improve the workflow and outcome of EVT.The CONTRAST consortium is supported by Netherlands Cardiovascular Research Initiative, an initiative of the Dutch Heart Foundation (CVON2015-01: CONTRAST) and by the Brain Foundation Netherlands (HA2015.01.06) and powered by Health∼Holland, Top Sector Life Sciences and receives unrestricted funding from Medtronic and Cerenovus. The collaboration project is additionally financed by the Ministry of Economic Affairs by means of the PPP Allowance made available by the Top Sector Life Sciences & Health to stimulate public-private partnerships (LSHM17016). This work was funded in part through unrestricted funding by Stryker, Medtronic and Cerenovus