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On the validation of an Evaluation Framework: Assessment by Experts

This report describes "a framework that delivers insight into the tangible and intangible effects of a mobile (IT) system, before it is being implemented".

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On the validation of an Evaluation Framework: Assessment by Experts

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On the validation of the initial step of an upfront system implementation evaluation framework:

This technical report describes "validation of the 'Target system definition"

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On the validation of the initial step of an upfront system implementation evaluation framework:

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The SOS-framework (Systems of Sedentary behaviours): an international transdisciplinary consensus framework for the study of determinants, research priorities and policy on sedentary behaviour across the life course

AbstractBackground: Ecological models are currently the most used approaches to classify and conceptualise determinantsof sedentary behaviour, but these approaches are limited in their ability to capture the complexity of and interplaybetween determinants. The aim of the project described here was to develop a transdisciplinary dynamic framework,grounded in a system-based approach, for research on determinants of sedentary behaviour across the life span andintervention and policy planning and evaluation.Methods: A comprehensive concept mapping approach was used to develop the Systems Of Sedentary behaviours(SOS) framework, involving four main phases: (1) preparation, (2) generation of statements, (3) structuring (sorting andranking), and (4) analysis and interpretation. The first two phases were undertaken between December 2013 andFebruary 2015 by the DEDIPAC KH team (DEterminants of DIet and Physical Activity Knowledge Hub). The lasttwo phases were completed during a two-day consensus meeting in June 2015.

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The SOS-framework (Systems of Sedentary behaviours): an international transdisciplinary consensus framework for the study of determinants, research priorities and policy on sedentary behaviour across the life course

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Reducing airport environmental footprint using a disruption-aware stand assignment approach

Modern airport management is challenged by the task of operating aircraft parking positions most efficiently while complying with environmental policies, restrictions, schedule disruptions, and capacity limitations. This study proposes a novel framework for the stand allocation problem that uses a divide-and-conquer approach in combination with Bayesian modelling, simulation, and optimisation to produce less-pollutant solutions under realistic conditions. The framework presents three innovative aspects. First, inputs from the stochastic analysis module are used in a multivariate optimisation for generating variability-robust solutions. Second, a combination of optimisation and simulation is used to finely explore the impact of realistic uncertainty uncaptured by the framework. Lastly, the framework considers the role of human beings as the final control of operational conditions. A case study is presented as a proof of concept and demonstrates results achievable and benefits of the framework proposed. The experimental results demonstrate that the framework generates less-pollutant solutions under realistic conditions.

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Reducing airport environmental footprint using a disruption-aware stand assignment approach

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P&ID-based automated fault identification for energy performance diagnosis in HVAC systems:

Current methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not consistent with process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to very limited application of energy performance diagnosis in practice. In a previous paper, a generic reference architecture – hereafter referred to as the 4S3F (four symptoms and three faults) framework – was developed. Because it is closely related to the way HVAC experts diagnose problems in HVAC installations, 4S3F largely overcomes the problem of limited application. The present article addresses the fault diagnosis process using automated fault identification (AFI) based on symptoms detected with a diagnostic Bayesian network (DBN). It demonstrates that possible faults can be extracted from P&IDs at different levels and that P&IDs form the basis for setting up effective DBNs. The process was applied to real sensor data for a whole year. In a case study for a thermal energy plant, control faults were successfully isolated using balance, energy performance and operational state symptoms. Correction of the isolated faults led to annual primary energy savings of 25%. An analysis showed that the values of set probabilities in the DBN model are not outcome-sensitive. Link to the formal publication via its DOI https://doi.org/10.1016/j.enbuild.2020.110289

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P&ID-based automated fault identification for energy performance diagnosis in HVAC systems:

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On the validation of an evaluation framework, the case of Nursemapp

This report describes the validation of a "framework that delivers insight into the tangible and intangible effects of a mobile (IT) system, before it is being implemented".

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On the validation of an evaluation framework, the case of Nursemapp

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SIM-OPT in the Loop: Algorithmic Framework for Solving Airport Capacity Problems

The following paper presents an innovative approach for dealing with complex capacity problems in aviation. We introduce a sliding window framework composed by an optimization method with a simulation component. By applying this framework in diverse problems that are dependent on time it is possible to find feasible and close-to-reality solutions in shorter time than the ones that could be achieved by evaluating the problem in the complete time-horizon. The framework can be applied to solve diverse problems in aviation or similar industries. We exemplify the approach with a model of Paris Charles de Gaulle Airport in France.

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The evaluation of fingermarks given activity level propositions

Fingermarks are highly relevant in criminal investigations for individualization purposes. In some cases, the question in court changes from ‘Who is the source of the fingermarks?’ to ‘How did the fingermark end up on the surface?’. In this paper, we explore evaluation of fingermarks given activity level propositions by using Bayesian networks. The variables that provide information on activity level questions for fingermarks are identified and their current state of knowledge with regards to fingermarks is discussed. We identified the variables transfer, persistency, recovery, background fingermarks, location of the fingermarks, direction of the fingermarks, the area of friction ridge skin that left the mark and pressure distortions as variables that may provide information on how a fingermark ended up on a surface. Using three case examples, we show how Bayesian networks can be used for the evaluation of fingermarks given activity level propositions.

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The evaluation of fingermarks given activity level propositions

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Modelling employee resilience using wearables and apps:

Occupational stress can cause health problems, productivity loss or absenteeism. Resilience interventions that help employees positively adapt to adversity can help prevent the negative consequences of occupational stress. Due to advances in sensor technology and smartphone applications, relatively unobtrusive self-monitoring of resilience-related outcomes is possible. With models that can recognize intra-individual changes in these outcomes and relate them to causal factors within the employee's context, an automated resilience intervention that gives personalized, just-in-time feedback can be developed. This paper presents the conceptual framework and methods behind the WearMe project, which aims to develop such models. A cyclical conceptual framework based on existing theories of stress and resilience is presented as the basis for the WearMe project. The operationalization of the concepts and the daily measurement cycle are described, including the use of wearable sensor technology (e.g., sleep tracking and heart rate variability measurements) and Ecological Momentary Assessment (mobile app). Analyses target the development of within-subject (n=1) and between-subjects models and include repeated measures correlation, multilevel modelling, time series analysis and Bayesian network statistics. Future work will focus on further developing these models and eventually explore the effectiveness of the envisioned personalized resilience system.

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Producten 115

On the validation of an Evaluation Framework: Assessment by Experts

On the validation of the initial step of an upfront system implementation evaluation framework:

The SOS-framework (Systems of Sedentary behaviours): an international transdisciplinary consensus framework for the study of determinants, research priorities and policy on sedentary behaviour across the life course

Reducing airport environmental footprint using a disruption-aware stand assignment approach

P&ID-based automated fault identification for energy performance diagnosis in HVAC systems:

On the validation of an evaluation framework, the case of Nursemapp

SIM-OPT in the Loop: Algorithmic Framework for Solving Airport Capacity Problems

The evaluation of fingermarks given activity level propositions

Modelling employee resilience using wearables and apps:

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Producten 115

On the validation of an Evaluation Framework: Assessment by Experts

On the validation of the initial step of an upfront system implementation evaluation framework:

The SOS-framework (Systems of Sedentary behaviours): an international transdisciplinary consensus framework for the study of determinants, research priorities and policy on sedentary behaviour across the life course

Reducing airport environmental footprint using a disruption-aware stand assignment approach

P&ID-based automated fault identification for energy performance diagnosis in HVAC systems:

On the validation of an evaluation framework, the case of Nursemapp

SIM-OPT in the Loop: Algorithmic Framework for Solving Airport Capacity Problems

The evaluation of fingermarks given activity level propositions

Modelling employee resilience using wearables and apps: