Unmanned Aerial Vehicles (UAVs) are widely used in the civil and commercial sectors, especially for their advantages in traffic control and logistics management. Due to their high mobility and flexible deployment capa...
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ISBN:
(纸本)9798350379860;9798350379877
Unmanned Aerial Vehicles (UAVs) are widely used in the civil and commercial sectors, especially for their advantages in traffic control and logistics management. Due to their high mobility and flexible deployment capability, UAVs have a significant role in traffic flow statistics, violation monitoring and traffic diversion. However, the security of link communication is challenged due to the openness of UAV wireless signals and the problem of co-channel interference. In this paper, we propose a UAV communication link enhancement scheme based on active security and design a new communication architecture to improve communication robustness and communication quality of service in heterogeneous network environments.
The Industrial Internet of Things (IIoT) has become an essential component of modern industrial automation. However, the security of IIoT remains a significant challenge due to its distributed and heterogeneous nature...
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Wireless communication networks operate over time-varying channels that depend on channel gains, power allocation algorithms, and inter-channel interference. In this paper, We present techniques for computing the opti...
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Wireless communication networks operate over time-varying channels that depend on channel gains, power allocation algorithms, and inter-channel interference. In this paper, We present techniques for computing the optimal control inputs, which lead to the attainment of the intended Signal to Interference plus Noise ratio (SINR) at different receivers. This optimization problem can be efficiently resolved using non-linear programming tools and permits the simultaneous assignment of multiple desired SINRs at different instances. We establish the conditions necessary to ensure the feasibility of the optimal control problem.
In this work, aconcentric elliptical array of antennas is optimized with the help of three relatively new and efficient meta-heuristic algorithms;namely, Teaching Learning Based Optimization (TLBO), Multi-Verse Optimi...
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The new power system is the national development strategy and development direction of smart grid. communication is the basis of the development of the new power system. in the distribution automation business, commun...
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ISBN:
(纸本)9781665455336
The new power system is the national development strategy and development direction of smart grid. communication is the basis of the development of the new power system. in the distribution automation business, communication is the weakest link. In order to make electric power communication develop more smoothly, we should improve our awareness of security issues. Because of the particularity of electric power communication, it often has very high requirements for the security of communication. In order to effectively ensure the security of electric power communication data, data encryption technology can be applied to the data transmission process, and the security of information transmission can be improved through the application of encryption and decryption keys. Physical layer key generation technology is a security technology that uses wireless channel characteristics as a random source to generate keys. This technology uses the anisotropy, time variation and spatial uniqueness of wireless channels to generate random sequences, which is different from traditional encryption methods. Physical layer key generation technology does not require the key management and distribution of a third party trusted organization. In theory, it can achieve one encryption at a time to achieve the absolute security of Shannon confidential communication[1]. This paper first briefly introduces the wireless channel physical layer key generation model and the general process of key generation scheme based on channel feature quantization, and then studies the improved optimization scheme based on traditional channel detection, preprocessing and quantization algorithm, so as to effectively improve the key generation performance.
Home automation is revolutionizing the way we look at conventional systems, however home automation is facing a problem as both controller and receiver have to be on same internet network to work properly. To resolve ...
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This project aims to develop a warehouse security system using an ESP32CAM, keypad, and Arduino UNO, LCD. The ESP32CAM is a powerful microcontroller that integrates Wi-Fi and a camera module, making it an ideal choice...
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In over modulated low voltage cascaded multi-level converters are subjected to power imbalance problems. The scheme of reactive power control is used to maintain the cascaded multilevel inverter under power imbalanced...
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Access control is an essential defensive tool businesses can use to satisfy both the legal requirements for data privacy and modern security concerns. It is intended to stop unauthorized people and systems from access...
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Human-machine function allocation or adaptive automation is an important means to achieve human-machine integration in human- machine collaboration systems. One of the purposes of human-machine function allocation met...
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ISBN:
(纸本)9798350379860;9798350379877
Human-machine function allocation or adaptive automation is an important means to achieve human-machine integration in human- machine collaboration systems. One of the purposes of human-machine function allocation methods is to maintain the operator's workload state in a reasonable state while realizing human-machine function allocation. Inspired by previous studies that widely used reinforcement learning methods for machine system control, this study modeled the automation level adjustment events in the human-machine interaction process using Markov decision processes. Taking the operator's physiological state that can be collected in real time during the human-machine interaction process as the model input and the automation level adjustment action as the output, a human-centered automation level adjustment model was established using the deep Q-network method. In addition, this study carried out a human-machine interaction experiment based on the flight control scenario to obtain data for training and validating the model. The results show that the model proposed in this study can better adjust the automation level of the system to maintain and balance the operator's workload state.
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