Critical Climate Machine is a cutting-edge media art installation that critically exposes and quantifies mechanisms of climate change misinformation. Utilizing computational aesthetics across data, imagery, and sound, this work processes real-time data ...

Dealing with many of the problems related to the quality of textual content online involves identifying similar content. Algorithmic solutions for duplicate content classification typically rely on text vector representation, which maps textual ...

Imbalanced data classification with Random Forest Classification (RFC) technique has gained huge prominence in today’s application era. Data imbalance between practical applications relates to either binary class imbalance or multiclass imbalance. ...

Over the past decades, rice crops are crucially admitted as one of the powerful energy streams for the production of resources. Rice plant diseases are considered as a raising factor behind the agricultural, economic and communal loss in the ...

The number of patents that are being filed across the world is increasing day by day. With the increase in patents being filed the process of segregating the patents based on their class becomes even more difficult. There are a set of features ...

The implementation of intelligent techniques produces good results in automating fault finding and predicting future outcomes. These approaches have been on the increase in the past years, especially so to detect faults within Compressed Air ...

In recent years, predictive maintenance tasks, especially for bearings, have become increasingly important. Solutions for these use cases concentrate on the classification of faults and the estimation of the Remaining Useful Life (RUL). As of ...

Network traffic classification plays a critical role in maintaining the security and efficiency of modern computer networks. Existing techniques often have problems effectively identifying and establishing network traffic patterns. This research seeks to ...

This paper explores the evolving landscape of electronic word-of-mouth (eWOM) and its impact on consumer behavior. With the transition from traditional word-of-mouth to online platforms (users’ reviews), businesses now have access to vast amounts of user-...

Coronary artery disease (CAD), in particular, stenosis, has been one of major causes of death from cardiac disease. Detecting the severity of stenosis, as well as localizing the distribution of stenosis in coronary artery have been urgent technical ...

This article provides a comprehensive survey of bias mitigation methods for achieving fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning bias mitigation for ML classifiers. These methods can be distinguished based ...

The exponential growth of audio data in radio broadcasts has generated the need for efficient tools for their manipulation and analysis to develop systems such as audio content classification and enhance user experience. In this study, we explore ...

Breast cancer is a disease that affects many women worldwide. Therefore, early detection of breast lesions is essential for effective diagnosis and treatment. In this context, digital breast tomosynthesis (DBT) is a promising technique for ...

Automatic sleep stage classification is important for measuring sleep quality. This paper is devoted to the implementation of a new attention-based deep learning architecture for staging sleep stages using single-channel EEG signals. And to research ...

A fist-sized organ that pumps blood throughout the human body is the heart or cardiac. Cardiac disease (CAD) is one of the deadliest diseases, threatening the lives of millions of people worldwide. Nowadays, several machine learning and deep learning ...

Blood malignancies and various blood disorders pose significant health challenges across all age groups. This study introduces adaptive fast fuzzy C means hybrid clustering (AFFCMHC) and binary adaptive Otsu (BAO) thresholding for image processing to ...

In this paper, we propose a MeowSorter that identifies stray and pet cats using deep learning technology, to address the problem that lost cats with owners are mistakenly identified as stray cats and wrongfully euthanized. We made a dataset of 800 facial ...

This paper investigates different techniques for binary classification in a multi-participant setting, with a focus on complex movement tasks. It uses statistical methods to extract features from pre-processed biosignals acquired by functional ...

With the development of exploration and trade, the coffee industry blossomed, and coffee gradually became an essential social drink for its unique taste and captivating aroma. Among various industrial coffee-producing processes, coffee bean ...

In order to fully extract spatial and elevation information for joint classification of hyperspectral image (HSI) and LiDAR (LiDAR) data, a multi-source remote sensing classification network based on multi-scale feature and attention mechanism is ...