Priority in task scheduling and resource allocation for cloud computing has attracted significant attention from the research community. However, traditional scheduling algorithms often lack the ability to differentiate between tasks with varying lev...
Many service providers often categorize their users into multi-classes, depending on their service requirements. Each class has strict quality of service (QoS) demands (e.g., minimum required service rate or transfer time) that must be ensured throug...
In indoor environments, the concentration of halogenated organic pollutants in dust can be high due to the presence of products treated with these chemicals. In this study, we monitored emerging organic pollutants, such as novel brominated flame reta...
Application areas that utilize the concept of IoT can be broadened to healthcare or remote monitoring areas. In this paper, a remote monitoring system for patients at home in IoT environments is proposed, constructed, and evaluated through several ex...
In this paper, multiclass classification is used to develop a novel approach to enhance failure mode and effects analysis and the generation of risk priority number. This is done by developing four machine learning models using auto machine learning....
A common practice in inventory systems with several customers requiring differentiated service levels is to group them into two or three classes, where a customer class is a group of customers with the same preset service level in terms of product av...
The media access control (MAC) protocol is a key element in the design of vehicular ad hoc networks (VANETs) that directly affects the network performance. The backoff schemes of existing MAC protocols apply the single backoff process and therefore a...
Road traffic injuries represent one of the most critical public health challenges in the Gulf region. Predicting traffic accident severity is therefore a critical component of evidence-based road safety management. In this study, we develop machine l...
Intrusion detection systems (IDSs) are commonly evaluated through aggregate classification metrics, although operational workflows require detected flows to be interpreted, prioritized, and transformed into actionable evidence. This study proposes a...
A single-server non-pre-emptive priority queueing system of a finite capacity with many types of customers is analyzed. Inter-arrival times can be correlated and batch arrivals are allowed. Possible unreliability of the server, implying the loss of a...
Today, the internet requires many additional mechanisms or protocols to support various ever-growing applications. As a future internet architecture candidate, the Named Data Network (NDN) offers a solution that naturally fulfills this need. One of t...
Radio Frequency Identification (RFID) is considered one of the pioneering technologies of the Internet of Things (IoT). It allows to bind physical environments to information processing systems, adding new capabilities like automatic inventorying, lo...
Vehicular Internet of Things (V-IoT) systems will be critical in advancing intelligent transportation networks because of the easy communication they make possible between vehicles, roadside infrastructure, and other network entities. Integrating ada...
Reliable counting of horticultural seeds is important for seed grading, batch consistency assessment, packaging, sowing-rate control, and post-harvest quality evaluation. Manual counting is labor-intensive, whereas conventional image-processing metho...
Machine learning (ML) algorithms are widely used in various fields, including cyber threat intelligence (CTI), financial technology (Fintech), and intrusion detection systems (IDSs). They automate security alert data analysis, enhancing attack detect...
Network slicing is a novel key technology in 5G networks which permits to provide a multitude of heterogeneous communication services over a common network infrastructure while satisfying strict Quality of Service (QoS) requirements. Since radio spec...
Exposure models are essential for seismic risk assessment to determine environmental vulnerabilities during earthquakes. However, developing these models at scale is challenging because it relies on manual inspection of buildings, which increases cos...
This study investigates the use of machine-learning approaches to interpret Dissolved Gas Analysis (DGA) data to find incipient faults early in oil-impregnated transformers. Transformers are critical pieces of equipment in transmitting and distributi...
Nanosatellites are proliferating as low-cost, dedicated remote sensing opportunities for small nations. However, nanosatellites’ performance as remote sensing platforms is impaired by low downlink speeds, which typically range from 1200 to 9600...
This paper presents the application of machine learning for classifying time-critical conditions namely sepsis, myocardial infarction and cardiac arrest, based off transcriptions of emergency calls from emergency services dispatch centers in South Af...
Server-side capacity dimensioning in operator-managed Over-The-Top (OTT) and Internet Protocol Television (IPTV) systems requires analytical methods that can account for heterogeneous traffic classes, differentiated subscription tiers, and strict gra...
Matching surgical patients to intensive care beds in real time remains stubbornly difficult in healthcare business operation. Demand spikes. Capacity tightens. Yet, even brief admission delays might trigger avoidable complications and inflate operati...
Alzheimer’s disease (AD) is a global health challenge requiring early and accurate diagnosis, yet current clinical methods struggle with early stages. Deep learning approaches for MRI-based diagnosis face persistent challenges related to image...
Rheum tanguticum (Maxim. ex Regel) Balf. is one of three botanical sources of Dahuang and exhibits chemical and processing variability that complicates species attribution and quality assessment. This review aims to synthesize species-specific phytoc...
21 November 2022
The rapid expansion of different types of urban land continues to erode natural and semi-natural ecological space and causes irreversible ecological damage to rapidly industrialized and urbanized areas. This work considers Quanzhou, a typical industr...
Transformer-based models have accelerated EEG motor imagery (MI) decoding by using self-attention to capture long-range temporal structures while complementing spatial inductive biases. This systematic survey of Scopus-indexed works from 2020 to 2025...
Invasive species significantly impact ecosystems, which is fostered by global warming. Their removal generates high costs to the greenery managers; therefore, quick and accurate identification methods can allow action to be taken with minimal impact...
While pesticides have become a primary tool in modern agriculture, these compounds remain a high priority on the list of consumer concerns regarding food safety. The use of pesticides in the production and post-harvesting of lemon fruits is widely us...
Smart cities increasingly rely on distributed sensing and edge intelligence to support urban planning, mobility management, environmental monitoring, and critical infrastructure operation. However, large-scale urban Internet-of-Things deployments are...