Sensor nodes are one of the basic elements in the Tactile Internet-based fog computing architecture. They provide a huge amount of data to the network due to the widespread real-world applications that use these types of wireless devices. This huge ...

Anomaly detection is a method for identifying malware and other anomalies such as memory leaks on computing hosts and, more recently, Internet of Things (IoT) devices. Due to its lightweight resource use and efficacy, anomaly detection is a promising ...

The history of neural networks dates back to the early 1940s and has not only evolved rapidly over time but they are now amongst one of the most popular and powerful machine learning techniques¹. In this area, graph representation learning (GRL) using ...

Data integration is considered a crucial task in the entity matching process. In this process, redundant and cunning entries must be identified and eliminated to improve the data quality. To archive this, a comparison between all entities is performed. ...

The data collected by public transport tickets has become a valuable source of information for transportation analysis. There are numerous works that analyze them in case studies for subway, bus or train networks, but there are few studies referring to ...

This paper presents a practical application of the method of using GPGPU calculations to estimate the level of human exposure on non-ionized EMF, especially deriving from mobile radiocommunication stations analyzed on wide-area territory (e.g. whole ...

International shipments always have a harmonized system code (HSCode) associated with them, to determine the tariff for the custom declaration. The HSCode is derived from the shipment description that the customer provides, which makes the quality of the ...

The fifth-generation (5G) of broadband cellular networks is giving rise to new paradigms of distributed computing, such as Edge Computing and Multi-access Edge Computing (MEC). The possibility of hosting Machine Learning (ML) applications close to the ...

This paper tackles the Campaign Allocation Problem of commercial Ads in TV breaks. The problem is NP-Hard and can be viewed as a multi-stakeholders multiobjective problem with highly competing objectives for different brands and numerous constraints. The ...

Nowadays Machine Learning (ML) techniques are extensively adopted in many socially sensitive systems, thus requiring to carefully study the fairness of the decisions taken by such systems. Many approaches have been proposed to address and to make sure ...

We present a proof-of-concept method for using bootstrapped learning for car detection in lidar scans using neural networks. We transfer knowledge from a traditional hand-engineered clustering and geometry-based detection technique to deep-learning-based ...

In this paper we aim to bring some order to the myriad of tools that have emerged in the field of Artificial Intelligence (AI), focusing on the field of Machine Learning (ML). For this purpose, we suggest a classification of the tools in which the ...