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Data driven discovery of systems of ordinary differential equations using nonconvex multitask learning
In physical sciences, dynamic systems are modeled using their parameters within governing equations that often form a system of ordinary differential...
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Unsupervised query-adaptive implicit subtopic discovery for diverse image retrieval based on intrinsic cluster quality
Given the complex search tasks imposed to social multimedia retrieval systems, the generated similarity-based ranked results often represent...
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FusionFlow: An Integrated System Workflow for Gene Fusion Detection in Genomic Samples
Gene fusion is a genomic alteration where two genes after a break event are juxtaposed to form a new hybrid gene, leading to possible cancer...
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A Technique for Collaboration Discovery
In the last years, researchers have contributed to the process mining domain with several techniques and tools supporting the discovery of business...
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Process Discovery Analysis for Generating RPA Flowcharts
Robotic Process Automation (RPA) is a frequently used approach for automation in IT systems. RPA uses existing graphical user interfaces to automate...
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ParslRNA-Seq: An Efficient and Scalable RNAseq Analysis Workflow for Studies of Differentiated Gene Expression
RNA sequencing has become an increasingly affordable way to profile gene expression analyses. Here we introduce a scientific workflow implementing...
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Pattern Discovery in Conceptual Models Using Frequent Itemset Mining
Patterns are recurrent structures that provide key insights for Conceptual Modeling. Typically, patterns emerge from the repeated modeling practice...
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Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models
Efficient methods for searching the chemical space of molecular compounds are needed to automate and accelerate the design of new functional...
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Recommendations for Data Discovery, Sensemaking and Reuse
In this chapter we synthesize and propose recommendations and areas for future work to support human-centered data discovery based on the literature...
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Revealing the Importance of Setting Parameters in Declarative Discovery Algorithms: An Evolutionary-Based Methodology
Through constraints, declarative process models represent the permitted behaviour associated with a business process, by limiting the potential...
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An Introduction to KDB: Knowledge Discovery in Biodiversity
The most basic method of experimentation using data mining algorithms is the command prompt. A convenient approach of interactive graphical user...
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Document-Based Knowledge Discovery with Microservices Architecture
The first step towards digitalization within organizations lies in digitization - the conversion of analog data into digitally stored data. This...
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Methods for explaining Top-N recommendations through subgroup discovery
Explainable Artificial Intelligence (XAI) has received a lot of attention over the past decade, with the proposal of many methods explaining black...
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Workflow
We have now defined the basic building blocks. The next step is to define how these building blocks move through the system, carrying data and...
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Knowledge graph model development for knowledge discovery in dementia research using cognitive scripting and next-generation graph-based database: a design science research approach
Recent studies report doubling numbers of deaths due to dementia. With such an escalating mortality rate related to cognitive decline diseases, like...
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Optimising Business Process Discovery Using Answer Set Programming
Declarative business process discovery aims at identifying sets of constraints, from a given formal language, that characterise a workflow by using...
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A cost-based multi-layer network approach for the discovery of patient phenotypes
Clinical records frequently include assessments of the characteristics of patients, which may include the completion of various questionnaires. These...
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Accelerating Drug Discovery in AutoDock-GPU with Tensor Cores
In drug discovery, molecular docking aims at characterizing the binding of a drug-like molecule to a macromolecule. AutoDock-GPU, a state-of-the-art...
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A hybrid multi-objective metaheuristic optimization algorithm for scientific workflow scheduling
Workflow is composed of some interdependent tasks and workflow scheduling in the cloud environment that refers to sorting the workflow tasks on...
