In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interacti...

In contrast with traditional modelling methods, which are used to identify parameter values of a model with known structure, equation discovery systems identify the structure of the model also. The model generated with such systems can give experts a better insight into the measured data and can be also used for predicting future values of the measured variables. This paper presents LAGRAMGE, a...

As the Web Services and Grid community adopt Semantic Web technology, we observe a shift towards higherlevel workflow composition and service discovery practices. While this provides excellent functionality to non-expert users, more sophisticated middleware is required to hide the details of service integration. By investigating a bioinformatics use case, we observe the need for Type Adaptor co...

This paper introduces the idea of using nonmonotonic inheritance networks for the storage and maintenance of knowledge discovered in data (revisable knowledge discovery in databases | RKDD). While existing data mining strategies for knowledge discovery in databases (KDD) typically involve initial structuring through the use of identiication trees and the subsequent extraction of rules from thes...

The vision of the Semantic Web is to reduce manual discovery and usage of Web resources (documents and services) and to allow intelligent agents to automatically identify these Web resources, integrate them and execute them for achieving the intended goals of the user. The composed Web service is represented as a workflow, called service flow. This paper presents different types of compositiona...

Mass cytometry (CyTOF) has greatly expanded the capability of cytometry. It is now easy to generate multiple CyTOF samples in a single study, with each sample containing single-cell measurement on 50 markers for more than hundreds of thousands of cells. Current methods do not adequately address the issues concerning combining multiple samples for subpopulation discovery, and these issues can be...

Background. Physical education learning in the era of the COVID-19 pandemic has a remarkable impact on students’ creativity. Objectives. This study aims to determine the effect of applying the inquiry and discovery models in online physical education learning to develop high school students’ creativity. Methods. The multiple treatment and control with the pre and post-test procedure were used...

Accelerating the discovery of new molecules and materials, as well developing green sustainable ways to synthesize them, will help address global challenges in energy, sustainability healthcare. The recent growth data science automated experimentation techniques has resulted advent self-driving labs (SDLs) via integration machine learning, lab automation robotics. An SDL is a machine-learning-a...

Probabilistic graphical models are being used widely in artiicial intelligence, for instance, in diagnosis and expert systems, as a uniied qualitative and quantitative framework for representing and reasoning with probabilities and independencies. Their development and use spans several elds including artiicial intelligence, decision theory and statistics, and provides an important bridge betwe...