A comprehensive review of cyber security vulnerabilities, threats, attacks, and solutions
Internet usage has grown exponentially, with individuals and companies performing multiple
daily transactions in cyberspace rather than in the real world. The coronavirus (COVID-19) …
daily transactions in cyberspace rather than in the real world. The coronavirus (COVID-19) …
Anomaly detection in 6G networks using machine learning methods
While the cloudification of networks with a micro-services-oriented design is a well-known
feature of 5G, the 6G era of networks is closely related to intelligent network orchestration …
feature of 5G, the 6G era of networks is closely related to intelligent network orchestration …
Performance Evaluation of Multi-Access Edge Computing for Blended Learning Services
Multi-access Edge Computing (MEC) is a technology that enables the deployment of cloud
computing capabilities at the edge of the network. It is an emerging technology that has …
computing capabilities at the edge of the network. It is an emerging technology that has …
Klasterisasi Data Jamaah Umrah pada Tanurmutmainah Tour Menggunakan Algoritma K-Means
Wisata religi khususnya umroh dan haji semakin diminati oleh masyarakat saat sekarang
ini. Tanurmutmainah Tour merupakan salah satu agen travel yang bergerak dibidang jasa …
ini. Tanurmutmainah Tour merupakan salah satu agen travel yang bergerak dibidang jasa …
Task reverse offloading with deep reinforcement learning in multi-access edge computing
The Multi-access Edge Computing (MEC) technology's quick development greatly benefits
the Collaborative Mobile Infrastructure System (CMIS). To combine the data and produce …
the Collaborative Mobile Infrastructure System (CMIS). To combine the data and produce …
[HTML][HTML] Energy Efficient CH Selection Scheme Based on ABC and Q-Learning Approaches for IoUT Applications
Nowadays, the Internet of Underwater Things (IoUT) provides many marine 5G applications.
However, it has some issues with energy efficiency and network lifetime. The network …
However, it has some issues with energy efficiency and network lifetime. The network …
Attacks Detection in 6G Wireless Networks using Machine Learning
Unlike the fifth generation (5G), which is well recognized for network cloudification with
micro-service-oriented design, the sixth generation (6G) of networks is directly tied to …
micro-service-oriented design, the sixth generation (6G) of networks is directly tied to …
Fractional Order Sequential Minimal Optimization Classification Method
C Zhao, L Dai, Y Huang - Fractal and Fractional, 2023 - mdpi.com
Sequential minimal optimization (SMO) method is an algorithm for solving optimization
problems arising from the training process of support vector machines (SVM). The SMO …
problems arising from the training process of support vector machines (SVM). The SMO …
Energy Efficient Path Planning Scheme for Unmanned Aerial Vehicle using Hybrid Generic Algorithm Based Q-Learning Optimization
Efficient path planning optimization strategies are required to maximize flying time while
consuming the least energy. This research offers a novel approach for energy-efficient path …
consuming the least energy. This research offers a novel approach for energy-efficient path …
[PDF][PDF] Enhancing urban mobility: integration of IoT road traffic data and artificial intelligence in smart city environment
I Moumen, J Abouchabaka… - Indonesian Journal of …, 2023 - pdfs.semanticscholar.org
Efficient traffic management poses a significant challenge in smart cities, requiring the
integration of diverse approaches. This paper presents an artificial intelligence framework …
integration of diverse approaches. This paper presents an artificial intelligence framework …