This study aims to evaluate energy efficiency in emerging economies. Within this context, a
hybrid fuzzy multi-criteria decision-making (MCDM) model is generated. In this model, firstly …

Detection of anomalous behaviors in data centers is crucial to predictive maintenance and
data safety. With data centers, we mean any computer network that allows users to transmit …

Power Quality (PQ) disturbances are critical in modern power systems, significantly
impacting electrical networks' stability, reliability, and efficiency. With the increasing …

We introduce a method called evolving Log Parsing (eLP) to extract information granules
and an interval rule-based classification model from streams of words in unstructured log …

This study focuses on how artificial intelligence (AI) can be used in education while
emphasizing the importance of adhering to European regulations requiring explanations of …

Emotion recognition has become a need for more realistic and interactive machines and
computer systems. The greatest challenge is the availability of high-performance algorithms …

Annually, the Large Hadron Collider (LHC) demands a huge amount of computing
resources to deal with petabytes of produced data. In the next years, a scheduled LHC …

The increasingly growing scale of modern computing infrastructures solicits more ingenious
and automatic solutions to their management. Our work focuses on file transfer failures …

This paper introduces a new multiclass classifier called the evolving Fuzzy Classifier (eFC).
Starting its knowledge base from scratch, the eFC structure evolves based on a clustering …

Intelligent systems for the medical domain often require processing data streams that evolve
over time and are only partially labeled. At the same time, the need for explanations is of …