An essential component of modern musculoskeletal rehabilitation systems is treadmills of various sizes, the control of which may rely either on manual adjustment of treadmill speed, fixed for the entire training session, or on automatic regulation ba...
This article describes a software environment called HybroGen, which helps to experiment binary code generation at run time. As computing architectures are getting more complex, the application performance is becoming data-dependent. The proposed exp...
Contemporary embedded systems may execute multiple applications, potentially concurrently on heterogeneous platforms, with different system workloads (CPU- or memory-intensive or both) leading to different power signatures. This makes finding the mos...
We identify the need for an easy-to-use self-driving simulator where game mechanics implicitly encourage high-quality data capture and an associated low-cost physical test platform. We design such a simulator incorporating environmental domain random...
Genotypic testing is often recommended to improve the management of patients infected with human immunodeficiency virus (HIV). To help combat this major pandemic, next-generation sequencing (NGS) techniques are widely used to analyse resistance to an...
The convolutional neural network (CNN) is one of the most used deep learning models for image detection and classification, due to its high accuracy when compared to other machine learning algorithms. CNNs achieve better results at the cost of higher...
Sparsity-based fault diagnosis methods have achieved great success. However, fault classification is still challenging because of neglected potential knowledge. This paper proposes a combined sparse representation deep learning (SR-DEEP) method for r...
This paper presents ReproRun, a flexible and extensible run-time framework for the reconfiguration of functions in field programmable gate array (FPGA) devices used in popular software-defined radio (SDR) platforms. The FPGA devices embed a hardwired...
Modern software systems need to autonomously adapt their behavior at runtime in order to maintain their utility in response to continuous environmental changes. Most studies on models at runtime focus on providing suitable techniques to manage the co...
Cyber-Physical Systems are experiencing a paradigm shift in which processing has been relocated to the distributed sensing layer and is no longer performed in a centralized manner. This approach, usually referred to as Edge Computing, demands the use...
With the recent development of artificial intelligence and data mining technology, various and intelligent vital sign analysis technologies have been developed. Vital sign analysis algorithms and technologies are primarily developed using MATLAB and...
The computational complexity of the multiple-input and multiple-output (MIMO) based least square algorithm is very high and it cannot be run on processing-inefficient low-cost platforms. To overcome complexity-related problems, a parallel distributed...
Recently, “Big Data” platform technologies have become crucial for distributed processing of diverse unstructured or semi-structured data as the amount of data generated increases rapidly. In order to effectively manage these Big Data, Cloud Computin...
This study aims to model training adaptation using Artificial Neural Network (ANN) geometric optimisation. Over 26 weeks, 38 swimmers recorded their training and recovery data on a web platform. Based on these data, ANN geometric optimisation was use...
The emerging serverless computing has become a captivating paradigm for deploying cloud applications, alleviating developers’ concerns about infrastructure resource management by configuring necessary parameters such as latency and memory const...
In the big data era, processing large amounts of data imposes several challenges, mainly in terms of performance. Complex operations in data science, such as deep learning, large-scale simulations, and visualization applications, can consume a signif...
Many software systems run on long-lifespan platforms that operate in diverse and dynamic environments. If these software systems could automatically adapt to hardware changes, it would significantly reduce the maintenance cost and enable rapid upgrad...
Most deep learning application studies have limited accessibility and reproducibility for researchers and students in many domains, especially in earth and climate sciences. In order to provide a step towards improving the accessibility of deep learn...
With the convergence of big data and HPC (high-performance computing), various machine learning applications and traditional large-scale simulations with a stochastically iterative I/O periodicity are running concurrently on HPC platforms, which pose...
Our study investigated the characteristics of the biomechanics of lower extremities during running single leg jump (RSJ) in collegiate basketball players. Twelve division III male basketball players voluntarily participated in this study. They perfor...
Brief face-to-face self-confidence workshops were effective in reducing depression among the public. Technological advances have enabled traditional face-to-face interventions to be adapted using unique technology-mediated platforms. This article det...
In this work, we conducted downward evacuation experiments in four types of staircases under various smoke visibility conditions of the naked eye, wearing sunglass and wearing eyeshades. Ten male and ten female college students were recruited to cond...
Immune therapy for cancer patients is a new and promising area that in the future may complement traditional chemotherapy. The cell expansion phase is a critical part of the process chain to produce a large number of high-quality, genetically modifie...
The approach running spike-jump (RSJ) is a crucial technique in the sport of volleyball. Two types of RSJs are commonly used for the volleyball spike attack: (1) RSJ with one leg (RSJ-1L) and (2) RSJ with two legs (RSJ-2L). The purposes of the curren...
Accurate and reliable estimation information of sideslip angle is very important for intelligent motion control and active safety control of an autonomous vehicle. To solve the problem of sideslip angle estimation of an autonomous vehicle, a sideslip...
Scientific applications often require substantial amount of computing resources for running challenging jobs potentially consisting of many tasks from hundreds of thousands to even millions. As a result, many institutions collaborate to solve large-s...
To achieve an immersive virtual reality (VR) environment, omnidirectional treadmills (ODTs) allow users to perform locomotion in any direction. However, existing ODTs are heavy and complex, and operate at low speeds. This limits fast user motion and...
This paper proposes a novel hybrid metaheuristic, called JADEGMO, that combines the adaptive parameter control of adaptive differential evolution with optional external archive (JADE) with the search strategies of geometric mean optimizer (GMO). The...
Current research about crowdsourcing covers industries like food systems or logistics, leaving out the possible impact of crowdsourcing on sustainable retail. The debate about the sustainable impact of different industries is ongoing, especially disc...
Applications are employing Near Field Communication (NFC) technology to interact with physical objects by using NFC tags. The architecture to implement these kinds of applications varies according to non-functional requirements such as the physical e...
With the advantages of wide range, constant observation ability, and an active imaging mechanism, synthetic aperture radar (SAR) has been a preferrable choice for ship detection in complicated scenarios. However, existing algorithms, especially for t...
Many connected devices are expected to be deployed during the next few years. Energy harvesting appears to be a good solution to power these devices but is not a reliable power source due to the time-varying nature of most energy sources. It is possi...
This paper presents the development and evaluation of EnnerSpectrum, a platform for electricity monitoring. The development was motivated by a gap between academic, fully custom-made monitoring solutions and commercial proprietary monitoring approach...
One of the problems encountered in the field of computer vision and video data analysis is the extraction of information from low-contrast images. This problem can be addressed in several ways, including the use of histogram equalisation algorithms....
Virtualization has been deployed as a key enabling technology for coping with the ever growing complexity and heterogeneity of modern computing systems. However, on its own, classical virtualization is a poor match for modern endpoint embedded system...
Participatory exposure research, which tracks behaviour and assesses exposure to stressors like air pollution, traditionally relies on time-activity diaries. This study introduces a novel approach, employing machine learning (ML) to empower layperson...
With the vigorous development of big data and cloud computing, containers are becoming the main platform for running applications due to their flexible and lightweight features. Using a container cluster management system can more effectively manage...
In recent decades, water scarcity has become a frequent and widespread phenomenon. Intensification of water scarcity will have economic impact on the main water-using sectors. The highest pressure on the water resources is exerted by agriculture. Irr...
The speed profile tracking calculation of high-speed maglev trains is mainly affected by running resistance. In order to reduce the adverse effects and improve tracking accuracy, this paper presents a maglev train operation control method based on a...
This paper presents the Parallel Primal-Dual (PPD3) algorithm, an innovative approach to solving optimization problems characterized by the minimization of the sum of three convex functions, including a Lipschitz continuous term. The proposed algorit...
Objective: Our objective was to investigate the biomechanical and neuromuscular adaptations of the lower limbs during the landing phase of running under fatigue conditions. Methods: A controlled fatigue protocol was used to induce running-related fat...
This paper presents accurate urban map generation using digital map-based Simultaneous Localization and Mapping (SLAM). Throughout this work, our main objective is generating a 3D and lane map aiming for sub-meter accuracy. In conventional mapping ap...
Belgium has actively participated in clinical research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since the beginning of the pandemic to help identify effective and safe treatments for COVID-19. The objective of this review is to...
With the rapid development of artificial intelligence technology in the field of intelligent manufacturing, convolutional neural networks (CNNs) have shown excellent performance and generalization capabilities in industrial applications. However, the...
This paper presents the architecture, implementation and evaluation of a middleware support layer for NoSQL storage systems. Our middleware automatically selects performance and scalability tactics in terms of application specific workloads. Enterpri...
Since the outbreak of the pandemic respiratory virus SARS-CoV-2 (COVID-19), academic communities and governments/private companies have used several detection techniques based on gold nanoparticles (AuNPs). In this emergency context, colloidal AuNPs...
Systems for application domains like robotics, aerospace, defense, autonomous vehicles, etc. are usually developed on System-on-Programmable Chip (SoPC) platforms, capable of supporting several multi-modal computation-intensive tasks on their FPGAs....
Applications running on the Internet of Things, such as the Wireless Sensor and Actuator Networks (WSANs) platform, generally have different quality of service (QoS) requirements. For urgent events, it is crucial that information be reported to the a...
This paper presents the results of numerical modeling and vibration testing of a nanosatellite’s optical payload, aimed at assessing its mechanical stability under the mechanical impacts of launch. The purpose of the study is to compare finite...
On GPU-based clusters, the training workloads of machine learning (ML) models, particularly neural networks (NNs), are often structured as Directed Acyclic Graphs (DAGs) and typically deployed for parallel execution across heterogeneous GPU resources...
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