Extreme Waves in the North Sea: Deriving extreme wave conditions applying Hierarchical Clustering and Non-Stationary Extreme Value Modelling

Coastal and offshore infrastructure must be designed to withstand extreme wave-induced loading conditions. Extreme Value Analysis (EVA) is often employed to infer probabilistic distributions that provide information about extreme design conditions. In traditional practices, EVA is performed under the assumption of stationarity. This means that...

Smooth, hierarchical competitor clustering using agglomerative hierarchical clustering

Clustering forms a major part of showing different relations between data points. Real-time clustering algorithms can visualise relationships between elements in a 3D environment, provide an analysis of data that is separate from the underlying structure and show how the data changes over time. <br/>This paper analyses whether conventional...

Interpretation of run-of-mine comminution and recovery parameters using multi-element geochemical data clustering

Multi-element (ME) datasets provide comprehensive geochemical signatures of an orebody and are commonly used to gain insight into the mineralogy, lithology, alteration patterns and to identify target-pathfinders. However, little effort is made in using these data to explain comminution or recovery characteristics. This paper describes an...

Developing efficient heuristic approaches to cluster editing, inspired by other clustering problems

Cluster editing attempts to find the minimum number of edge additions and removals on an undirected graph, that will transform the graph to one consisting of only disconnected cliques. In this paper, we propose three heuristic approaches to this problem, based on algorithms used to solve different clustering problems. The algorithms were based...

Improving Test Case Generation for REST APIs Through Hierarchical Clustering

With the ever-increasing use of web APIs in modern-day applications, it is becoming more important to test the system as a whole. In the last decade, tools and approaches have been proposed to automate the creation of system-level test cases for these APIs using evolutionary algorithms (EAs). One of the limiting factors of EAs is that the...

Beyond connecting the dots: A multi-scale, multi-resolution approach to marine habitat mapping

Conflicts of interests between economic and nature conservation stakeholders are increasingly common in coastal seas, inducing a growing need for evidence-based marine spatial planning. This requires accurate, high-resolution habitat maps showing the spatial distribution of benthic assemblages and enabling intersections of habitats and...

Automated offline detection of disruptions using smart card data: A case study of the metro network of Washington DC

Service reliability is one of the most important performance measures to public transport users. Detecting disruptions helps to measure service reliability, which can be used by public transport operators to improve this reliability. In this thesis, a methodology is described to automatically detect disruptions offline, using smart card data....

Dynamic and interactive re-formulation of multi-objective optimization problems for conceptual architectural design exploration

Simulation-Based Multi-Objective Optimization (SBMOO) methods are being increasingly used in conceptual architectural design. They mostly focus on the solving, rather than the re-formulation, of a Multi-Objective Optimization (MOO) problem. However, Optimization Problem Re-Formulation (Re-OPF) is necessary for treating ill-defined conceptual...

Windfalls from Extractive Activities in Colombia: A Support for Regional Growth and Development?

Authors such as Clough (1955) and Rostow (1960) believed that countries endowed with natural resources could achieve sustainable economic growth. This belief was based on the role coal and oil had during the 19th and 20th century in the industrial development of countries such as Australia, Canada and the United States of America. However, this...

Detecting mixed Mycobacterium tuberculosis infections and differences in drug susceptibility with WGS data

Tuberculosis is a pulmonary disease caused by the pathogen Mycobacterium tuberculosis and is the second leading cause of death from an infectious disease. Individuals infected by multiple strains referred to as a mixed infection are associated with poor treatment outcomes when the infecting strains differ in their susceptibility against...

Spatial-temporal pathline clustering based on FTLE fields

Cardiac flow acquisition is a young and ongoing field of research which provides us with a vast amount of unsteady 3D blood flow data of the heart (4D vector fields). These 4D vector fields of the heart are used in clinical research to gain insight in the flow patterns within the heart which in turn can be used to gain a better understanding of...