Intelligent reflecting surface (IRS) has recently gained significant academic interest as a prospective contender for improving wireless communication system coverage and spectral efficiency. This paper investigates a...
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Intelligent reflecting surface (IRS) has recently gained significant academic interest as a prospective contender for improving wireless communication system coverage and spectral efficiency. This paper investigates a robust beamforming design of an IRS-aided dual-functional radar-communication (DFRC) system in the presence of channel uncertainty, as opposed to the idealistic assumption of perfect channel state information (CSI) in the existing literature. The optimization is carried out by minimizing the transmit power while ensuring the detection performance and the achievable rate of the user meets the quality of service (QoS) requirement, which turns out to be a non-convex and intractable problem. To circumvent this issue, we alternatively update the transmit beamforming vector and the phase shifts at the IRS using the block coordinate descent (BCD) algorithm. Afterwards, the resulting two sub-problems can be efficiently solved with the help of approximation and transformation techniques. Simulation results have validated the convergence and effectiveness of the proposed algorithm.
Cloud computing has changed the paradigm of using computing resources. It has shifted from traditional storage and computing to Internet based computing leveraging economy of scale, cost saving, elimination of data re...
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3D view reconstruction in a real-time unknown environment poses several challenges to vision-based applications. Herein, this paper outlines real-time experimental results and analysis of 3D view reconstruction method...
3D view reconstruction in a real-time unknown environment poses several challenges to vision-based applications. Herein, this paper outlines real-time experimental results and analysis of 3D view reconstruction methods. Since real-time experimentation requires inputs from different sensors, this paper outlines the results of methods from the following categories: image based methods and point cloud based methods. This paper explains the detailed steps involved in 3D view reconstruction followed by an explanation of the methods. It provides detailed discussions, advantages, limitations, and empirical results, along with presenting differences between algorithms. For analysis of experimental results, two benchmarked datasets i.e., KITTI 3D benchmark suite and ShapeNet are considered. Furthermore, the paper explores potential future scopes, including the utilization of generative models, unsupervised learning, advanced sensors, and many more.
The world is now more connected than it has ever been. Billions of smartphones, laptops, servers and other devices communicate with each other over the internet every second of every day. One place where IoT devices c...
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Face detection applications currently can use machine learning and equations for better identification of human faces in an image or video. In several types of applications such as recognition of face application that...
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The gradual advancements towards the development of Deep Neural Networks has ultimately led to the development of certain specialised hardware for the application of such Networks with superior performance. But, many ...
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In this 21st century, ensuring the security of a place is one of the most crucial things. We have to use either manual or semi-autonomous entrances and human security guards in most of the security systems. Many sophi...
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At the nexus of quantum computing and machine learning, quantum machine learning (QML) and quantum deep learning (QDL) have emerged as promising fields. By enhancing computational capabilities and addressing challengi...
At the nexus of quantum computing and machine learning, quantum machine learning (QML) and quantum deep learning (QDL) have emerged as promising fields. By enhancing computational capabilities and addressing challenging data analysis problems, these approaches have the potential to revolutionise a number of domains by leveraging the special properties of quantum systems, such as superposition and entanglement. In this article, we give a thorough analysis of QML and QDL algorithms, discussing their underlying ideas, benefits over conventional models, and potential uses. We talk about the difficulties these algorithms face, such as noisy quantum hardware, constrained qubit resources, training and optimisation issues, input representation and data encoding problems, and limited interpretability. Additionally, we look at current developments and lines of inquiry that aim to address these issues, including hybrid classical-quantum methods, error-mitigating techniques, better data representation techniques, quantum transfer learning, and resource optimisation.
Phishing is a typical assault on unsuspecting individuals by making them to reveal their one-of-a-kind data utilizing fake sites. The target of phishing site URLs is to purloin the individual data like client name, pa...
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Drunk driving continues to be a substantial public health issue, leading to a multitude of accidents and deaths on a global scale. Conventional techniques for identifying drunk driving, such as breathalyzers and field...
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ISBN:
(数字)9798331530471
ISBN:
(纸本)9798331530488
Drunk driving continues to be a substantial public health issue, leading to a multitude of accidents and deaths on a global scale. Conventional techniques for identifying drunk driving, such as breathalyzers and field sobriety tests, tend to be reactive rather than proactive. This paper surveys the existing methods for detecting drunk driving to enhance traffic safety. The technologies studied can proactively detect impaired driving behaviors by combining machine learning (ML) approaches with real-time data processing. The study outlines various classifications based on measured metrics and driving behavior.
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