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Frost is the condition that exists when the temperature of the earth's surface and earthbound objects falls below freezing (0°C). These events may have serious consequences on crop production, so actions must be taken t...

"Gravitatonal waves, the seed of the 2015 Nobel’s prize are the cause of several complex celestial phenomena that is non-observable for the naked eye. Their identification, classification and study is s(ll a handmade w...

As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on o...

This book is a material aimed at training new graduates and updating practising professionals within the framework of early childhood care (0-6 years). It also opens up training to new professions such as health engineer...

Several interdisciplinary studies highlight imperfect information as a possible explanation of skill mismatches, which in turn has implications for unemployment and informality rates. Despite information failures and the...

We are pleased to present to the entire academic community and the general public the following work, which contains recent research results of a group of teachers from the Faculty of Educational Sciences in areas such a...

"This paper presents a supervised classification method to accurately detect epileptic brain activity in real-time from electroencephalography (EEG) data. The proposed method has three main strengths: it has low computat...

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of documents in digital form and the ensuing n...

The European Union (EU) is actively working to combat climate change and promote sustainable development by reducing greenhouse gas (GHG) emissions. The transport sector, a major contributor of GHG emissions, was at the ...

The problem of unwanted e-mails (or spam messages) has been increasing for years. Different methods have been proposed in order to deal with this problem wich includes blacklists of known spammers, handcrafted rules and ...

"The steel industry faces increasing challenges in managing product diversity, maintaining competitiveness, and improving operational efficiency. Within this context, recommendation systems present a promising opportunit...

A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. However, in many real-world applications, this...

In cases of extremely imbalanced dataset with high dimensions, standard machine learning techniques tend to be overwhelmed by the large classes. This paper rebalances skewed datasets by compressing the majority class. Th...

In an industrial maintenance context, degradation diagnosis is the problem of determining the current level of degradation of operating machines based on measurements. With the emergence of Machine Learning techniques, s...

We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning tec...

DNA Microarrays are powerful tools to analyze and identify certain disease from the expression level of the genes in tissues samples. Many machine learning techniques are suitable for building predictive models to classi...

We apply machine learning techniques to the automatic classification of news articles from the local newspaper La Capital of Rosario, Argentina. The corpus (LCC) is an archive of approximately 75,000 manually categorized...

"In order to evaluate the relation between KC and memory processes our main goal was to create a method with Machine Learning techniques to characterize and identify KCs."

This paper presents a system that can take short messages relevant to a particular topic from a microblogging service such as Twitter or Facebook, analyze the messages for the sentiments they carry on, and classify them....

"Identificar la actividad cerebral epiléptica utilizando señales de electroencefalografía (EEG) en tiempo real es un problema difícil. Los métodos modernos de detección basados en técnicas avanzadas de aprendizaje...

Numerical Taxonomy aims to group in clusters, using so-called structure analysis of operational taxonomic units (OTUs or taxons or taxa) through numerical methods. Clusters that consitute families was the purpose of this...

Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex dev...

This work presents a systematic literature review on the application of Machine Learning algorithms in the development of effective movie recommender systems. With the increasing popularity of movie recommender systems i...

Machine learning and data mining techniques have been used in numerous real-world applications. An assumption of traditional machine learning methodologies is the training data and testing data are taken from the same do...