Due to the limited onboard power and bandwidth resources, multibeam satellite communication technology requires efficient resource allocation algorithms to meet the demands of satellite communication for smart girds. ...
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Due to the limited onboard power and bandwidth resources, multibeam satellite communication technology requires efficient resource allocation algorithms to meet the demands of satellite communication for smart girds. A resource allocation model considering inter-beam interference and electric service delay is proposed in this paper. The Improved Coyote Optimization Algorithm (ICOA), in which the original COA is enhanced based on the Whale Optimization Algorithm to accelerate the solving speed, is applied to minimize the fairness index. Simulation experiments demonstrate that this algorithm has a significant advantage in both speed and fairness index during the solving process.
In a network environment that become more complex due to the continuous update of emerging Internet technologies, distributed denial of service (DDoS) attacks also become easier to implement and more difficult to dete...
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In a network environment that become more complex due to the continuous update of emerging Internet technologies, distributed denial of service (DDoS) attacks also become easier to implement and more difficult to detect. Such as in the blockchain environment, the performance of node equipment is often low, the deployment cost of existing detection systems is high, and multi-point collaborative detection cannot be performed. In response to these problems, this paper proposes a lightweight DDoS attack detection method based on LightBGM. The paper proposes a multi-component network traffic feature group to extract the features of network flow to realize the lightweight of DDoS attack detection on the feature input. The experimental results show that the proposed feature group can describe the network flow more accurately. Compared with other DDoS attack detection methods, LightGBM-based methods have higher accuracy, recall and prediction rates, lower error rate and missing rate, while occupying less computing resources.
Always-on AI sensor applications-based on deep neural networks (DNNs)-with sparse inference require low power consumption during both computing and idle phases. Inmemory computing (IMC) with non-volatile memory crossb...
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The Creation of Vehicle-to-Grid technology was driven by the rise of electric vehicles and grid concerns with regard to renewable energy sources. The suggested system outlines the push-pull inverter based V2G, which i...
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In modern avionics system Testing and Verification are very important criteria. With the advantage of Field Programmable Gate Array (FPGA), power sub systems are more intelligent with advance features. Advance power s...
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The paper focuses on hardware implementation of a reduced-cost, high-performance chopper-based four-quadrant DC drive system. The main aim is to control the speed and direction of a DC motor efficiently across all fou...
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Compact and integrated 220GHz solid-state power amplifiers (SSPAs) are important in enabling future high-data-rate wireless communication, imaging, and radar systems. Silicon (CMOS and SiGe) and III-V (GaAs and InP) t...
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Due to sheer global energy crisis, concerns about fuel deuteriation, electricity shortages, power quality enhance and global warming are the major challenges becoming increasingly severe. The tremendous scarcity of co...
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This didactic paper explores topological superconductivity, an essential idea for enhancing topological quantum computing by utilizing Majorana Fermions (Majorana Zero Modes). Topological quantum computing can enable ...
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ISBN:
(纸本)9783031734762;9783031734779
This didactic paper explores topological superconductivity, an essential idea for enhancing topological quantum computing by utilizing Majorana Fermions (Majorana Zero Modes). Topological quantum computing can enable fault-tolerant qubits, which are essential for implementing quantum AI algorithms and related techniques. This paper discusses the basic principles of topological superconductors, their experimental implementations, and the crucial importance of Majorana Fermions in facilitating error-resistant quantum computing. The paper also examines the integration of quantum AI, emphasizing how the stability of topological qubits enhances the performance of quantum machine learning algorithms. It discusses the obstacles and future possibilities of using topological states for quantum technologies, focusing on engineering applications and recent technical advancements. The study highlights the potential of topological superconductivity to transform quantum computing by providing insight into the creation of reliable quantum systems and scalable quantum circuits.
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