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Learning classifier systems (LCSs) are a state-of-the-art methodology for developing rule-based machine learning by applying discovery algorithms and learning components. LCSs have become proficient at linking environmental features to describe simple ...

Urdu, characterized by its intricate morphological structure and linguistic nuances, presents distinct challenges in computational sentiment analysis. Addressing these, we introduce ”UrduAspectNet” – a dedicated model tailored for Aspect-Based Sentiment ...

Datacenter applications desire low latency for short messages to provide a better user experience. Therefore, one of the goals of datacenter networks is to minimize flow completion time (FCT), especially for short flows. Multiple scheduling ...

Machine learning is playing an increasingly important role in education. This article examines its potential to bring about transformative change in this field. By using machine learning algorithms, physical education teachers can gather and analyze data ...

Nurses, often considered the backbone of global health services, are disproportionately vulnerable to COVID-19 due to their front-line roles. They conduct essential patient tests, including blood pressure, temperature, and complete blood counts. ...

• Introducing Deep Ensemble of Adaptive Architectures for COVID-19 patient detection.
• Utilizing an ensemble of seven models to enhance patient detection accuracy.
• Integrating detected images with soft robots for essential patient ...

Self-energy recycling cooperative communication, in which the relay nodes simultaneously harvest energy from the source and their own transmitted signal, has been demonstrated to significantly increase the total harvested energy. In this paper, we ...

Cooperative communication is key in attaining high network throughput and better coverage area for a wireless powered communication network. The conventional solution methodologies proposed in the literature for these networks suffer from high ...

Deep learning is a cutting-edge methodology that has been widely used in real-world applications to solve computer vision tasks. Deep learning models are typically seen as black boxes, opaque, and difficult to interpret. Recently, attention-based vision ...

Device-to-device (D2D) communication has become a key complementary technology in emerging next-generation communication paradigm. It offers a number potential use cases including peer to peer communication, cellular offloading, device-relaying ...

Wireless powered communication networks (WPCNs) will act as a major enabler of massive machine type communications (MTCs), which is a major service domain for 5G and beyond systems. The MTC networks will be deployed by using low-power transceivers with ...

Underwater image classification is a challenging task because of challenging underwater environment and lighting conditions. We propose a novel learning classifier system (LCS), which can classify large-size underwater images with promising ...

Cell classification refers to detecting normal and diseased cells from small amount of data. Sometimes, classification of cells becomes difficult because some cells fall into more than one categories/classes. Current state‐of‐the‐art cell ...

A framework of the proposed method NDCC (normal and diseased cell classification), used traditional machine learning and deep learning. image image

The emerging fifth generation (5G) and beyond radio access networks are expected to be extremely dense and heterogeneous as compared to the current networks, involving a large number of different classes of base stations (BSs), namely macro, micro,...

We consider a relay based full-duplex wireless powered cooperative communication network which consists of a hybrid access point (HAP), N users and K decode-and-forward relays with energy harvesting capability. We propose an optimization framework ...

Video camera sensor networks (VCSN) has numerous applications in smart cities, including vehicular networks, environmental monitoring, and smart houses. Scheduling of video camera sensor networks (VCSN) can reduce the computational complexity, ...

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• ‐We mathematically model scheduling of VCSNs for IoT systems.
• ‐We have used a probabilistic learning method by minimizing the Kullback Leibler (KL) distance/divergence.
• ‐We evaluated the performance of the CEO for scheduling of VCSNs in terms ...

RNA 5-methylcytosine (m⁵C) sites perform a major role in numerous biological processes and commonly reported in both DNA and RNA cellular. The enzymatic mechanism and biological functions of m⁵C sites in DNA remain the focusing area of researchers ...

Emerging device‐centric communication technologies such as device‐to‐device (D2D) communication, devices‐to‐device (Ds2D) communication, and multi‐homing (MH) D2D have been considered as essential parts of future fifth‐generation networks as well ...

image image In this article, a new method for device‐centric communication in IoT system is introduced, where multiple source IoT devices(SIDs) can send data to multiple destination IoT devices (DIDs) using multiple radio resource blocks. This method is ...

In this study, we consider a wireless powered communication network where multiple users with radio frequency energy harvesting capabilities communicate to a hybrid energy and information access point in full duplex mode. We characterize an ...

In this paper, an energy cost minimization framework is presented for a green cellular network. The proposed novel energy cooperation scheme ensures optimal energy cooperation among grid-connected green cellular base stations (BSs). The framework ...

Device to device (D2D) communication technique is one of the established means to enhance data rate in next generation wireless systems. Use of same resource of cellular users by D2D pairs creates interference problem among users. Simultaneous ...