Search results for "Heuristic"
showing 10 items of 476 documents
On Big Data: How should we make sense of them?
2020
The topic of Big Data is today extensively discussed, not only on the technical ground. This also depends on the fact that Big Data are frequently presented as allowing an epistemological paradigm shift in scientific research, which would be able to supersede the traditional hypothesis-driven method. In this piece, I critically scrutinize two key claims that are usually associated with this approach, namely, the fact that data speak for themselves, deflating the role of theories and models, and the primacy of correlation over causation. In so doing, I will also refer to a recent case history of data mining projects in the field of biomedicine, i.e. EXPOsOMICS. My intention is both to acknow…
Collective agency and the concept of ‘public’ in public involvement: A practice-oriented analysis
2016
Background Public involvement activities are promoted as measures for ensuring good governance in challenging fields, such as biomedical research and innovation. Proponents of public involvement activities include individual researchers as well as non-governmental and governmental organizations. However, the concept of ‘public’ in public involvement deserves more attention by researchers because it is not purely theoretical: it has important practical functions in the guidance, evaluation and translation of public involvement activities. Discussion This article focuses on collective agency as one property a public as a small group of participants in a public involvement activity could exhib…
A practical approach to improve the statistical performance of surface water monitoring networks
2019
The representativeness of aquatic ecosystem monitoring and the precision of the assessment results are of high importance when implementing the EU’s Water Framework Directive that aims to secure a good status of waterbodies in Europe. However, adapting monitoring designs to answer the objectives and allocating the sampling resources effectively are seldom practiced. Here, we present a practical solution how the sampling effort could be re-allocated without decreasing the precision and confidence of status class assignment. For demonstrating this, we used a large data set of 272 intensively monitored Finnish lake, coastal, and river waterbodies utilizing an existing framework for quantifying…
Combining workload balance and patient priority maximisation in operating room planning through hierarchical multi-objective optimisation
2022
Abstract Previous analysis suggested the opportunity to consider the preferences of different stakeholders (hospital, patients, doctors and nurses) through the adoption of both patient priority maximisation and workload balance as performance criteria. The aim of this paper is to develop an effective and efficient solution approach for the operating room planning and scheduling capable to take into account the patient priority maximisation and workload balance criteria at the same time. This work is inspired by the need of a deeper understanding of the quality of the solutions obtained when a combination of the two criteria leads the OR planning decisions. Starting from a hierarchical multi…
Heuristic Solutions for a Class of Stochastic Uncapacitated p-Hub Median Problems
2019
In this work, we propose a heuristic procedure for a stochastic version of the uncapacitated r-allocation p-hub median problem with nonstop services. In particular, we assume that the number of hubs to which a terminal can be allocated is bounded from above by r. Additionally, we consider the possibility of shipping traffic directly between terminals (nonstop services). Uncertainty is associated with the traffic to be shipped between nodes and with the transportation costs. If we assume that such uncertainty can be captured by a finite set of scenarios, each of which with a probability known in advance, it is possible to develop a compact formulation for the deterministic equivalent proble…
Stability-Based Model Selection for High Throughput Genomic Data: An Algorithmic Paradigm
2012
Clustering is one of the most well known activities in scien- tific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is the model selection problem, i.e., the identifi- cation of the correct number of clusters in a dataset. In the last decade, a few novel techniques for model selection, representing a sharp departure from previous ones in statistics, have been proposed and gained promi- nence for microarray data analysis. Among those, the stability-based methods are the most robust and best performing in terms of predic- tion, but the slowest in terms of time. Unfortunately…
GenClust: A genetic algorithm for clustering gene expression data
2005
Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a) a novel coding of the search space that is simple, …
A framework to identify primitives that represent usability within Model-Driven Development methods
2014
Context: Nowadays, there are sound methods and tools which implement the Model-Driven Development approach (MDD) satisfactorily. However, MDD approaches focus on representing and generating code that represents functionality, behaviour and persistence, putting the interaction, and more specifically the usability, in a second place. If we aim to include usability features in a system developed with a MDD tool, we need to extend manually the generated code. Objective: This paper tackles how to include functional usability features (usability recommendations strongly related to system functionality) in MDD through conceptual primitives. Method: The approach consists of studying usability guide…
A Proposal for Modelling Usability in a Holistic MDD Method
2014
Holistic methods for Model-Driven Development (MDD) aim to model all the system features in a conceptual model. This conceptual model is the input for a model compiler that can generate software systems by means of automatic transformations. However, in general, MDD methods focus on modelling the structure and functionality of systems, relegating the interaction and usability features to manual implementations at the last steps of the software development process. Some usability features are strongly related to the functionality of the system and their inclusion is not so easy. In order to facilitate the inclusion of functional usability features from the first steps of the development proc…
Tabu search for min-max edge crossing in graphs
2020
Abstract Graph drawing is a key issue in the field of data analysis, given the ever-growing amount of information available today that require the use of automatic tools to represent it. Graph Drawing Problems (GDP) are hard combinatorial problems whose applications have been widely relevant in fields such as social network analysis and project management. While classically in GDPs the main aesthetic concern is related to the minimization of the total sum of crossing in the graph (min-sum), in this paper we focus on a particular variant of the problem, the Min-Max GDP, consisting in the minimization of the maximum crossing among all egdes. Recently proposed in scientific literature, the Min…