Oxidative stress produced in response to infection or sterile injury activates the innate immune
response. We found that extracellular vesicles (EVs) isolated from the plasma of patients …

Recent trends in the development of autonomous vehicles focus on real-time processing of
vast amounts of data from various sensors. The data can be acquired using multiple cameras…

Klasteryzacja danych jest czesto wykorzystywanym narzedziem analizy w wielu dziedzinach
nauki. Wazny, choc czesto zaniedbywany etap klasteryzacji to ocena wyników tego rodzaju …

Damage-associated endogenous molecules induce innate immune response, thus making
sterile inflammation medically relevant. Stress-derived extracellular vesicles (stressEVs) …

Clustering-ensemble methods have emerged recently as an effective approach to the problem
of clustering, which is one of the fundamental data-analysis tools. Data clustering with an …

Data clustering is the fundamental data analysis method, widely used for solving problems
in the field of machine learning. Numerous clustering algorithms exist, based on various …

Over the last decade, the advent of the cluster ensemble framework has enabled more
accurate and robust data analysis than traditional single clustering algorithms. The improved …

To improve efficiency and reduce costs, industry rapidly adopts the concepts promoted by
Industry 4.0 paradigm. For the future engineers it is important to meet these concepts already …

In the thesis we address all the major stages of data clustering: data generation, data analysis
using single-clustering algorithms, cluster validity using internal and external indices, and …

Clustering or cluster analysis is a fundamental machine learning task, which is, unfortunatelly,
an ill-posed problem, caused by large diversity of problem domains. Many different …