Skip to Content

Computers, Volume 11, Issue 5

2022 May - 26 articles

Cover Story: Using brain–computer interfaces (BCI), brain activity signals can be acquired, preprocessed, and classified in order to then be utilized in various fields of application such as prosthetics, robot control, or even entertainment. The extracted brain features and their classification method play crucial roles in the system’s ability to obtain and retain high robustness and efficiency. In this paper, we perform research to identify the most robustly effective approaches in the field of motor imagery (MI) BCIs. The results show that wavelet transforms combined with deep learning achieved the highest scores in terms of robustness and performance. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
  • You may sign up for email alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.

Articles (26)

  • Article
  • Open Access
17 Citations
5,237 Views
15 Pages

How Machine Learning Classification Accuracy Changes in a Happiness Dataset with Different Demographic Groups

  • Colm Sweeney,
  • Edel Ennis,
  • Maurice Mulvenna,
  • Raymond Bond and
  • Siobhan O’Neill

This study aims to explore how machine learning classification accuracy changes with different demographic groups. The HappyDB is a dataset that contains over 100,000 happy statements, incorporating demographic information that includes marital statu...

  • Article
  • Open Access
29 Citations
5,297 Views
21 Pages

Botanical Leaf Disease Detection and Classification Using Convolutional Neural Network: A Hybrid Metaheuristic Enabled Approach

  • Madhumini Mohapatra,
  • Ami Kumar Parida,
  • Pradeep Kumar Mallick,
  • Mikhail Zymbler and
  • Sachin Kumar

Botanical plants suffer from several types of diseases that must be identified early to improve the production of fruits and vegetables. Mango fruit is one of the most popular and desirable fruits worldwide due to its taste and richness in vitamins....

  • Communication
  • Open Access
8 Citations
2,942 Views
13 Pages

Energy Efficiency of IoT Networks for Environmental Parameters of Bulgarian Cities

  • Zlatin Zlatev,
  • Tsvetelina Georgieva,
  • Apostol Todorov and
  • Vanya Stoykova

Building modern Internet of Things (IoT) systems is associated with a number of challenges. One of the most significant among them is the need for wireless technology, which will serve to build connectivity between the individual components of this t...

  • Article
  • Open Access
36 Citations
6,069 Views
12 Pages

Comparison of Statistical and Machine-Learning Models on Road Traffic Accident Severity Classification

  • Paulo Infante,
  • Gonçalo Jacinto,
  • Anabela Afonso,
  • Leonor Rego,
  • Vitor Nogueira,
  • Paulo Quaresma,
  • José Saias,
  • Daniel Santos,
  • Pedro Nogueira and
  • Paulo Rebelo Manuel
  • + 3 authors

Portugal has the sixth highest road fatality rate among European Union members. This is a problem of different dimensions with serious consequences in people’s lives. This study analyses daily data from police and government authorities on road...

  • Article
  • Open Access
25 Citations
11,070 Views
17 Pages

This article proposes a new concept of microservice-based architecture for the future of distributed systems. This architecture is a bridge between Internet-of-Things (IoT) devices and applications that are used to monitor cattle health in real time...

  • Article
  • Open Access
36 Citations
10,385 Views
20 Pages

A Real Time Arabic Sign Language Alphabets (ArSLA) Recognition Model Using Deep Learning Architecture

  • Zaran Alsaadi,
  • Easa Alshamani,
  • Mohammed Alrehaili,
  • Abdulmajeed Ayesh D. Alrashdi,
  • Saleh Albelwi and
  • Abdelrahman Osman Elfaki

Currently, treating sign language issues and producing high quality solutions has attracted researchers and practitioners’ attention due to the considerable prevalence of hearing disabilities around the world. The literature shows that Arabic S...

  • Article
  • Open Access
9 Citations
4,467 Views
13 Pages

QoS-Aware Scheduling Algorithm Enabling Video Services in LTE Networks

  • Amal Abulgasim Masli,
  • Falah Y. H. Ahmed and
  • Ali Mohamed Mansoor

The Long-Term Evolution (LTE) system was a result of the 3rd-Generation Partnership Project (3GPP) to assure Quality-of-Service (QoS) performance pertaining to non-real-time and real-time services. An effective design with regards to resource allocat...

  • Article
  • Open Access
5 Citations
6,316 Views
13 Pages

Multicore and multithreaded architectures increase the performance of computing systems. The increase in cores and threads, however, raises further issues in the efficiency achieved in terms of speedup and parallelization, particularly for the real-t...

  • Article
  • Open Access
1 Citations
4,606 Views
17 Pages

Performance analysis plays an essential role in achieving a scalable performance of applications on massively parallel supercomputers equipped with thousands of processors. This paper is an empirical investigation to study, in depth, the performance...

  • Article
  • Open Access
2,705 Views
17 Pages

In the domain of artificial neural networks, it is important to know what their representation, classification and generalization capabilities are. There is also a need for time and resource-efficient training algorithms. Here, a new zero-error train...

  • Article
  • Open Access
4 Citations
3,552 Views
21 Pages

Data imbalance is a serious problem in machine learning that can be alleviated at the data level by balancing the class distribution with sampling. In the last decade, several sampling methods have been published to address the shortcomings of the in...

  • Article
  • Open Access
29 Citations
8,087 Views
13 Pages

Emotion Recognition in Human–Robot Interaction Using the NAO Robot

  • Iro Athina Valagkouti,
  • Christos Troussas,
  • Akrivi Krouska,
  • Michalis Feidakis and
  • Cleo Sgouropoulou

Affective computing can be implemented across many fields in order to provide a unique experience by tailoring services and products according to each person’s needs and interests. More specifically, digital learning and robotics in education c...

  • Article
  • Open Access
16 Citations
6,763 Views
28 Pages

The presented research study focuses on demonstrating the learning ability of a neural network using a genetic algorithm and finding the most suitable neural network topology for solving a demonstration problem. The network topology is significantly...

  • Article
  • Open Access
4 Citations
3,057 Views
13 Pages

Traffic and transportation forecasting is a key issue in urban planning aimed to provide a greener and more sustainable environment to residents. Their privacy is a second key issue that requires synthetic travel data. A possible solution is offered...

  • Article
  • Open Access
7 Citations
3,421 Views
19 Pages

The emerging 5G mobile networks are essential enablers for mobile virtual reality (VR) video streaming applications assuring high quality of experience (QoE) at the end-user. In addition, mobile edge computing brings computational resources closer to...

  • Article
  • Open Access
3 Citations
4,291 Views
21 Pages

We present our experience with developing active learning activities in a collaborative teacher setting, along with guidelines for teachers to create them. We focus on developing learner skills in colours, design, and visualisation. Typically, teache...

  • Article
  • Open Access
57 Citations
5,980 Views
18 Pages

IoTwins: Toward Implementation of Distributed Digital Twins in Industry 4.0 Settings

  • Alessandro Costantini,
  • Giuseppe Di Modica,
  • Jean Christian Ahouangonou,
  • Doina Cristina Duma,
  • Barbara Martelli,
  • Matteo Galletti,
  • Marica Antonacci,
  • Daniel Nehls,
  • Paolo Bellavista and
  • Daniele Cesini
  • + 1 author

While the digital twins paradigm has attracted the interest of several research communities over the past twenty years, it has also gained ground recently in industrial environments, where mature technologies such as cloud, edge and IoT promise to en...

  • Article
  • Open Access
21 Citations
3,781 Views
34 Pages

Metaheuristic Extreme Learning Machine for Improving Performance of Electric Energy Demand Forecasting

  • Sarunyoo Boriratrit,
  • Chitchai Srithapon,
  • Pradit Fuangfoo and
  • Rongrit Chatthaworn

Electric energy demand forecasting is very important for electric utilities to procure and supply electric energy for consumers sufficiently, safely, reliably, and continuously. Consequently, the processing time and accuracy of the forecast system ar...

  • Article
  • Open Access
7 Citations
5,570 Views
17 Pages

Comparison of REST and GraphQL Interfaces for OPC UA

  • Riku Ala-Laurinaho,
  • Joel Mattila,
  • Juuso Autiosalo,
  • Jani Hietala,
  • Heikki Laaki and
  • Kari Tammi

Industry 4.0 and Cyber-physical systems require easy access to shop-floor data, which allows the monitoring and optimization of the manufacturing process. To achieve this, several papers have proposed various ways to make OPC UA (Open Platform Commun...

  • Article
  • Open Access
17 Citations
3,965 Views
18 Pages

A Transfer-Learning-Based Novel Convolution Neural Network for Melanoma Classification

  • Mohammad Naved Qureshi,
  • Mohammad Sarosh Umar and
  • Sana Shahab

Skin cancer is one of the most common human malignancies, which is generally diagnosed by screening and dermoscopic analysis followed by histopathological assessment and biopsy. Deep-learning-based methods have been proposed for skin lesion classific...

  • Article
  • Open Access
2 Citations
3,385 Views
14 Pages

Reactive programming is a popular paradigm that has been used as a new solution in our proposed model for security in the cloud. In this context, we have been able to reduce the execution time compared to our previous work for the model proposed in c...

  • Article
  • Open Access
3 Citations
2,623 Views
16 Pages

The problem of patient admission scheduling (PAS) is a nondeterministic polynomial time (NP)-hard combinatorial optimization problem with numerous constraints. Researchers have divided the constraints of this problem into hard (i.e., feasible solutio...

  • Review
  • Open Access
8 Citations
4,705 Views
19 Pages

Motor Imagery Brain Computer Interfaces (MI-BCIs) are systems that receive the users’ brain activity as an input signal in order to communicate between the brain and the interface or an action to be performed through the detection of the imagin...

  • Article
  • Open Access
16 Citations
4,993 Views
24 Pages

Application Prospects of Blockchain Technology to Support the Development of Interport Communities

  • Patrizia Serra,
  • Gianfranco Fancello,
  • Roberto Tonelli and
  • Lodovica Marchesi

A key aspect for the efficiency and security of maritime transport is linked to the associated information flows. The optimal management of maritime transport requires the sharing of data in real-time between the various participating organizations....

  • Article
  • Open Access
7 Citations
5,550 Views
20 Pages

Digital Game-Based Support for Learning the Phlebotomy Procedure in the Biomedical Laboratory Scientist Education

  • Tord Hettervik Frøland,
  • Ilona Heldal,
  • Turid Aarhus Braseth,
  • Irene Nygård,
  • Gry Sjøholt and
  • Elisabeth Ersvær

Practice-based training in education is important, expensive, and resource-demanding. Digital games can provide complementary training opportunities for practicing procedural skills and increase the value of the limited laboratory training time in bi...

  • Article
  • Open Access
3 Citations
3,524 Views
26 Pages

Foot-to-Ground Phases Detection: A Comparison of Data Representation Formatting Methods with Respect to Adaption of Deep Learning Architectures

  • Youness El Marhraoui,
  • Hamdi Amroun,
  • Mehdi Boukallel,
  • Margarita Anastassova,
  • Sylvie Lamy,
  • Stéphane Bouilland and
  • Mehdi Ammi

Identifying the foot stance and foot swing phases, also known as foot-to-ground (FTG) detection, is a branch of Human Activity Recognition (HAR). Our study aims to detect two main phases of the gait (i.e., foot-off and foot-contact) corresponding to...

XFacebookLinkedIn
Computers - ISSN 2073-431X