Several maintenance tasks in industrial sectors involve dealing with analogue devices, often performed manually by a worker, leaving no evidence of the task being done and prone to human error. A typical device found in this environment is the analogue ...

This paper introduces an end-to-end trainable power line communication (PLC) system based on a deep neural network (DNN). PLC channels are challenging to be modeled and estimated because of uncertain loads in utility / power grids, heterogeneous network ...

An immense volume of data is produced by sensor devices in the fields of aquaponics, hydroponics, and soil-based food production, where these devices track various environmental factors. Data stream mining is the method of retrieving data from fast-...

Ceramics is a millenary industrial sector with relevant financial impact for several countries. Efficiency in color mixing is crucial in the ceramic industry, both in terms of staff time and consumables costs. Traditional color mixing methods usually ...

Action recognition has become a prerequisite approach to fluent Human-Robot Interaction (HRI) due to a high degree of movement flexibility. With the improvements in machine learning algorithms, robots are gradually transitioning into more human-populated ...

Widespread plant illnesses have a negative influence on crop production, so it is important to diagnose them timely otherwise there is possibility that they can spread speedily and dramatically lower crop output. Corn is the second-most prevalent cereal ...

Data preprocessing is a crucial step in every data science project. In many real-world use cases, it is practical for efficiency reasons to combine multiple numeric target variables into one model whenever the input features are the same. However, the ...

With the progress of sensor technology in wearables, the collection and analysis of PPG signals are gaining more interest. Using Machine Learning, the cardiac rhythm corresponding to PPG signals can be used to predict different tasks such as activity ...

Due to global warming, Arctic sea ice is now declining, and this loss is a self-accelerating process that speeds up sea ice melting and the severity of climate change. Accurate and timely sea ice information is critically important for better monitoring ...

The need for artificial intelligence systems to expose reasons for promoted decisions grows with the prevalence of these systems in society. In this work, we study, for carefully selected images, how an end user’s trust is affected by visual ...

The COVID-19 pandemic has changed the daily lives of all people worldwide, affecting not only society but also various sectors such as finance, tourism, etc. To counteract the pandemic, measures are required to detect contagions and take the necessary ...

Most of the existing techniques for solving data imbalance problems are geared towards binary classification problems, hence a novel strategy capable of natively handling multi-class classification problems is required. Existing implementations mainly ...

Learning the syntax and structure of command-line commands is of utmost importance in the field of cyber security to identify valid and malicious sets of commands. It is hard to learn the syntax and structure of every command because of various reasons, ...

For developing nations like Bangladesh, the Calamity of Energy, one of the most important warnings experienced in the modern world, is a significant problem. Solar energy is a great solution for the future. When solar panels are used to create ...

Machine learning (ML) algorithms are increasingly important for the success of products and services, especially considering the growing amount and availability of data. This also holds for areas handling sensitive data, e.g. applications processing ...

The increasingly rich and diverse applications of sensors in industry as well as in commercial products require flexible, accurate, and long-term dependable integrated electronics realizations. To achieve this goal, the future sensors in Industry 4.0 ...