Integrating multicriteria decision analysis and scenario planning : review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country

Biology-guided algorithms:Improved cardiovascular risk prediction and biomarker discovery

Medical research has seen a stark increase in the amount of available data. The sheer volume and complexity of measured variables challenge the use of traditional statistical methods and are beyond the ability of any human to comprehend. Solving this problem demands powerful models capable of capturing the variable interactions and how those are non-linearly related to the condition under study. In this thesis, we first use Machine Learning (ML) methods to achieve better cardiovascular risk prediction/disease biomarker identification and then describe novel bio-inspired algorithms to solve some of the challenges. On the clinical side, we demonstrate how combining targeted plasma proteomics with ML models outperforms traditional clinical risk factors in predicting first-time acute myocardial infarction as well as recurrent atherosclerotic cardiovascular disease. We then shed some light on the pathophysiological pathways involved in heart failure development using a multi-domain ML model. To improve prediction, we develop a novel graph kernel that incorporates protein-protein interaction information, and suggest a manifold mixing algorithm to increase inter-domain information flow in multi-domain models. Finally, we address global model interpretability to uncover the most important variables governing the prediction. Permutation importance is an intuitive and scalable method commonly used in practice, but it is biased in the presence of covariates. We propose a novel framework to disentangle the shared information between covariates, making permutation importance competitive against methodologies where all marginal contributions of a feature are considered, such as SHAP

User benefits and funding strategies

The justification, economic and technological benefits of NASA Space Programs (aside from pure scientific objectives), in improving the quality of life in the United States is discussed and outlined. Specifically, a three-step, systematic method is described for selecting relevant and highly beneficial payloads and instruments for the Interim Upper Stage (IUS) that will be used with the space shuttle until the space tug becomes available. Viable Government and private industry cost-sharing strategies which would maximize the number of IUS payloads, and the benefits obtainable under a limited NASA budget were also determined. Charts are shown which list the payload instruments, and their relevance in contributing to such areas as earth resources management, agriculture, weather forecasting, and many others

A service network perspective to evaluate service matching in early design

Purpose – Service matching is defined in this paper as the process of combining a new service with one or more existing services. A recurring problem for service designer is to match new services with existing ones. This process may be seen as the fundamental action for the development of a service network. The purpose of this paper is to evaluate the consequences that may follow from service matching. Design/methodology/approach – Through an analogy with living organisms in natural ecosystems, the service relationship deployment (SRD) allows the investigation of the possible relationships between matched services. Findings – This paper presents a new method, named SRD, developed to support the process of service matching in the early design phases of a new service. The description of the method is supported by some practical examples. Originality/value – The focus of the scientific community on the problem of matching new services with existing ones, is very limited. This paper proposes a new methodology to address this issue