Social media has emerged as a pivotal platform for individuals to convey their thoughts and emotions, making it imperative for businesses, governments, and organizations to leverage artificial intelligence, such as se...
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Special vehicles often need to keep the body level quickly and accurately when carrying out follow-up control or missile launch. In order to enhance the mobility of the special vehicle during the leveling process, thi...
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The fault current caused by a high impedance fault is not sufficient to trigger overcurrent protection relays, which may lead to serious power accidents, fires, or even explosions in the distribution network, resultin...
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Small signal model of PWM converters are derived from averaging method. In the case of resonant converters, the averaging method fails because tank currents and voltages have no dc component. Moreover, the phenomenon ...
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In this paper, a Power Flow (PF) algorithm for a Power Distribution System (DS) derived from the conventional backward-forward sweep method is simulated with the integration of Solar Photovoltaic (SPV) based distribut...
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In dynamic and unpredictable work environments such as manufacturing, logistics, and automated warehouses, achieving high-precision self-localization estimation for efficient object picking are critical challenges for...
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We discuss the main concepts and problems related to navigating an unmanned aerial vehicle (UAV) in a three-dimensional space via visual odometry. In the nearest future, GMSS-free UAV navigation will embody a critical...
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We discuss the main concepts and problems related to navigating an unmanned aerial vehicle (UAV) in a three-dimensional space via visual odometry. In the nearest future, GMSS-free UAV navigation will embody a critical part of autonomous navigation systems, with information from on-board cameras enabling the user to estimate the UAV’s movement and position. In the given context, this paper presents different types of visual odometry, sensors for visual odometry, implementation components, and application scenarios. To allow the development and innovations, we utilize the widely used Robotic Operating System (ROS).
Bangladesh faces a significant power shortage, prompting the need for renewable energy solutions in residential areas. This study analyzes the energy load of a three-story residential building and designs a grid-conne...
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The finite rate of innovation (FRI) of certain signal classes allows for sub-Nyquist sampling, while modulo folding enables sampling signals with dynamic ranges beyond that of an analog-to-digital converter (ADC). Com...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
The finite rate of innovation (FRI) of certain signal classes allows for sub-Nyquist sampling, while modulo folding enables sampling signals with dynamic ranges beyond that of an analog-to-digital converter (ADC). Combining these techniques enables sampling at sub-Nyquist rates using an ADC with a lower dynamic range than the signal. Current signal recovery techniques use algorithmic approaches with high oversampling factors (OFs) and constraints on the signal parameters. In this paper, we introduce a deep learning method to modulo unfolding and combine it with an annihilating filter approach for signal parameter recovery. Our method significantly improves unfolding accuracy and reduces error compared to the state-of-the-art, and performs well at OFs as low as 2 times the rate of innovation, with no constraints on the signal parameters. This approach offers a practical tool for signal recovery from modulo sampled FRI signals, potentially reducing the hardware demands of measurement devices.
The Internet of Vehicles (IoV), as one subset of the Internet of Things (IoT) in the smart transportation area, integrates vehicle networks with sensors and actuators. By connecting all sensors to the network, the IoV...
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ISBN:
(数字)9798350384611
ISBN:
(纸本)9798350348439
The Internet of Vehicles (IoV), as one subset of the Internet of Things (IoT) in the smart transportation area, integrates vehicle networks with sensors and actuators. By connecting all sensors to the network, the IoV enables smart transportation (i.e., autonomous vehicles) and makes smart cities a reality. In smart transportation systems, roadside units (RSUs) capture all vehicle information and serve as gateways. However, smart transportation infrastructure has yet to mature in the current stage. RSUs are insufficient to support all vehicles. Meanwhile, the low computational capability of vehicles makes it challenging to recompute the driving route as the road environment changes. To address the problem of insufficient RSU coverage, one protocol called IEEE 802.11p enables vehicle-to-vehicle communication using relays. Nonetheless, data transfer among vehicles via relays is still time-consuming for a large-scale transportation network. To deal with the above issues, in this paper, we propose an IoV framework using digital twins (DTs) to digitize the IoV environment and assign nearby IoT gateways compatible with the RSU communication protocol. This framework lets DTs update the vehicle’s driving route based on real-time information. With a case study, we evaluate the efficacy of DT-assisted IoV based on communication latency and vehicle driving efficiency. Our evaluation results confirm that the proposed framework can efficiently enhance communication latency when the relay needs to pass through two or more vehicles and reduce travel time when vehicles receive updated route information at intersections.
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