Yayıncı "ELSEVIER" Bilgisayar Mühendisliği Bölümü Koleksiyonu için listeleme
Toplam kayıt 20, listelenen: 1-20
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AI-based fog and edge computing: A systematic review, taxonomy and future directions
(ELSEVIER, 2023)Resource management in computing is a very challenging problem that involves making sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse nature of workload, and the unpredictability of ... -
Big datasets of optical-wireless cyber-physical systems for optimizing manufacturing services in the internet of things-enabled industry 4.0
(ELSEVIER, 2022)The Industry 4.0 revolution is aimed to optimize the prod- uct design according to the customers’ demand, quality re- quirements and economic feasibility. Industry 4.0 employs advanced two-way communication technologies ... -
Cloud Computing for Smart Grid applications
(ELSEVIER, 2014)A reliable and efficient communications system is required for the robust, affordable and secure supply of power through Smart Grids (SG). Computational requirements for Smart Grid applications can be met by utilizing the ... -
Comparison of QoS-aware single-path vs. multi-path routing protocols for image transmission in wireless multimedia sensor networks
(ELSEVIER, 2014)Wireless multimedia sensor network (WMSN) applications require strong multimedia communication competence. Therefore, in WMSN applications, it is necessary to use specific mechanisms in order to handle multimedia communication ... -
CoviDetector: A transfer learning-based semi supervised approach to detect Covid-19 using CXR images
(ELSEVIER, 2023)COVID-19 was one of the deadliest and most infectious illnesses of this century. Research has been done to decrease pandemic deaths and slow down its spread. COVID-19 detection investigations have utilised Chest X-ray ... -
Deep learning approaches for vehicle type classification with 3-D magnetic sensor
(ELSEVIER, 2022)In the Intelligent Transportation Systems, it is crucial to determine the type of vehicles to improve traffic management, increase human comfort, and enable future development of transport infrastructures. This paper presents ... -
A deep neural network approach with hyper-parameter optimization for vehicle type classification using 3-D magnetic sensor
(ELSEVIER, 2023)The identification of vehicle types plays a critical role in Intelligent Transportation Systems. In this study, battery-operated, easy-to-install, low-cost 3-D magnetic traffic sensors have been developed for vehicle type ... -
An effective colorectal polyp classification for histopathological images based on supervised contrastive learning
(ELSEVIER, 2024)Early detection of colon adenomatous polyps is pivotal in reducing colon cancer risk. In this context, accurately distinguishing between adenomatous polyp subtypes, especially tubular and tubulovillous, from hyperplastic ... -
An efficient network intrusion detection approach based on logistic regression model and parallel artificial bee colony algorithm
(ELSEVIER, 2024)In recent years, the widespread use of the Internet has created many issues, especially in the area of cybersecurity. It is critical to detect intrusions in network traffic, and researchers have developed network intrusion ... -
Energy consumption of on-device machine learning models for IoT intrusion detection
(ELSEVIER, 2023)Recently, Smart Home Systems (SHSs) have gained enormous popularity with the rapid development of the Internet of Things (IoT) technologies. Besides offering many tangible benefits, SHSs are vulnerable to attacks that ... -
Ensemble feature selection and classification methods for machine learning-based coronary artery disease diagnosis
(ELSEVIER, 2023)Coronary artery disease (CAD) is a condition in which the heart is not fed sufficiently as a result of the accumulation of fatty matter. As reported by the World Health Organization, around 32% of the total deaths in the ... -
Intelligent traffic light systems using edge flow predictions
(ELSEVIER, 2024)In this paper, we propose a novel graph-based semi-supervised learning approach for traffic light management in multiple intersections. Specifically, the basic premise behind our paper is that if we know some of the occupied ... -
Intrinsic graph topological correlation for graph convolutional network propagation
(ELSEVIER, 2022)Recently, Graph Convolutional Networks (GCNs) and their variants become popular to learn graph-related tasks. These tasks include link prediction, node classification, and node embedding, among many others. In the node ... -
Machine learning approaches for underwater sensor network parameter prediction
(ELSEVIER, 2023)Underwater Acoustic Sensor Networks (UASNs) have recently attracted scientists due to its wide range of real -world applications. However, there are design challenges in UASNs, such as limited network lifetime and low ... -
Networking and communications for smart cities special issue editorial
(ELSEVIER, 2015)Our society is facing an unprecedented massive urbanization. At the time of writing, 54% of the world’s population lives in urban areas (with an 82% peak in North America), opposed to only 30% in 1950. Reports [1] predict ... -
On the interdependency between multi-channel scheduling and tree-based routing for WSNs in smart grid environments
(ELSEVIER, 2014)Field tests show that the link-quality of wireless links in different smart grid environments, such as outdoor substation, varies greatly both in space and time because of various factors, including multi-path, fading, ... -
Quality-of-service differentiation in single-path and multi-path routing for wireless sensor network-based smart grid applications
(ELSEVIER, 2014)Electrical grid is one of the most important infrastructure of the modern nation. However, power grid has been aged over 100 years and prone to major failures. The imbalance between power demand and supply, the equipment ... -
A reliable and secure multi-path routing strategy for underwater acoustic sensor networks
(ELSEVIER, 2022)Underwater Acoustic Sensor Networks (UASNs) have nowadays become an attractive topic in scientific studies and commercial applications. An important challenge in UASN’s design is the limited network lifetime and ... -
A review of on-device machine learning for IoT: An energy perspective
(ELSEVIER, 2024)Recently, there has been a substantial interest in on-device Machine Learning (ML) models to provide intelligence for the Internet of Things (IoT) applications such as image classification, human activity recognition, ... -
Routing protocol design guidelines for smart grid environments
(ELSEVIER, 2014)The evaluation of the current electric power grid with novel communication facilities is one of the most challenging and exciting issues of the 21st century. The modern grid technology is called the smart grid in the sense ...