This manuscript presents a comparative study of FPGA and GPU architectures, highlighting their contributions to enhancing the computing power of integrated circuits. It emphasizes the significance of computing power a...
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The increasing impacts of climate change on agriculture necessitates a shift towards adaptive solutions, with Climate-Smart Agriculture (CSA) emerging as a pivotal paradigm. This study underscores the imperative trans...
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ISBN:
(纸本)9798350372113;9798350372106
The increasing impacts of climate change on agriculture necessitates a shift towards adaptive solutions, with Climate-Smart Agriculture (CSA) emerging as a pivotal paradigm. This study underscores the imperative transition from conventional farming to CSA by shedding light on multi-faceted applications of IOT-based weather stations. This article details the design, development, and implementation of a lowcost weather station integrated with a control system, driven by Arduino Mega. This system also includes cloud- based and edg-ebased data transmission capabilities enabling real-time data monitoring for the farmers and efficient data collection. In the context of precision agriculture and smart farming, this study aims to achieve the goals of meteorological innovations, cost-effectiveness, customizability, and scalable solutions for diverse applications such as weather monitoring, climate forecasting, pesticide spray, CO2 injection, and automated irrigation. Results and discussions showcase the system's capabilities in capturing meteorological data, including CO2 concentration, solar irradiation, wind speed, wind direction, and rainfall. The study concludes by highlighting the flexibility and scalability of the designed system, with potential applications extending beyond environmental monitoring to encompass irrigation control, plant health monitoring, and overall productivity enhancement.
From the Turing Machine in the late 1930s which was hypothesized to be capable of simulating any algorithmic computation to modern computers that can execute intricate computations, the progress in computing has been ...
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This paper uses a method based on the YOLOv5s network to study the real-time traffic light detection task in the vehicle-mounted intelligent system. Due to the limitation of computing resources on the actual vehicle a...
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This paper describes how the kinematic configuration of a driving simulator's motion system affects the rendered inertial motion. The specific force and rotational rate equations between the point where the motion...
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ISBN:
(纸本)9798350399462
This paper describes how the kinematic configuration of a driving simulator's motion system affects the rendered inertial motion. The specific force and rotational rate equations between the point where the motion is applied (Motion Reference Point (MRP)), and the point in which the driver perceives the motion (Cueing Reference Point (CRP)), are derived for three kinematic configurations: (i) a hexapod, (ii) a hexapod with an xy-drive and a yaw-drive below, and (iii) the same system as (ii), but with the yaw-drive on top. The rotational rate equations show that having a yaw-drive on top greatly complicates the motion control. Furthermore, simulation results show that, regardless of the yaw-drive location, the difference between MRP and CRP becomes noticeable for large yawdrive excitations. For such driving simulators, the positional offset between MRP and CRP can therefore not be ignored, complicating the motion control.
When developing safety-critical control applications such as autonomous driving, it is crucial to assess the impact of model uncertainties on the system's closed-loop behaviour. Various methods, referred to as unc...
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ISBN:
(纸本)9798350399462
When developing safety-critical control applications such as autonomous driving, it is crucial to assess the impact of model uncertainties on the system's closed-loop behaviour. Various methods, referred to as uncertainty quantification, are available in the literature with different levels of accuracy and computational costs. This paper investigates and compares the application of different uncertainty quantification techniques based on the Unscented Transformation and the Polynomial Chaos Expansion to a highway lane change manoeuvre in a closed-loop setting. The resulting means and standard deviations of the trajectory error of the closedloop system are compared with the corresponding Monte-Carlo estimates, which serve as ground truth. It turns out that the Unscented Transformation provides accurate results at moderate computational costs and is best suitable for real-time deployment.
In the evolving landscape of urban mobility, the prospective integration of Connected and Automated Vehicles (CAVs) with Human-Driven Vehicles (HDVs) presents a complex array of challenges and opportunities for autono...
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ISBN:
(纸本)9798350377712;9798350377705
In the evolving landscape of urban mobility, the prospective integration of Connected and Automated Vehicles (CAVs) with Human-Driven Vehicles (HDVs) presents a complex array of challenges and opportunities for autonomous driving systems. While recent advancements in robotics have yielded Multi-Agent Path Finding (MAPF) algorithms tailored for agent coordination task characterized by simplified kinematics and complete control over agent behaviors, these solutions are inapplicable in mixed-traffic environments where uncontrollable HDVs must coexist and interact with CAVs. Addressing this gap, we propose the Behavior Prediction Kinematic Priority Based Search (BK-PBS), which leverages an offline-trained conditional prediction model to forecast HDV responses to CAV maneuvers, integrating these insights into a Priority Based Search (PBS) where the A* search proceeds over motion primitives to accommodate kinematic constraints. We compare BK-PBS with CAV planning algorithms derived by rule-based car-following models, and reinforcement learning. Through comprehensive simulation on a highway merging scenario across diverse scenarios of CAV penetration rate and traffic density, BK-PBS outperforms these baselines in reducing collision rates and enhancing system-level travel delay. Our work is directly applicable to many scenarios of multi-human multi-robot coordination.
With the development of modern technology, people are paying more and more attention to intelligent devices. And sound source localization is an important component of many intelligent devices, which enable the device...
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The proceedings contain 28 papers. The topics discussed include: power marketing based on deep reinforcement learning can explain large data mining methods;design and implementation system and statistical model for pr...
ISBN:
(纸本)9798331506261
The proceedings contain 28 papers. The topics discussed include: power marketing based on deep reinforcement learning can explain large data mining methods;design and implementation system and statistical model for precision evaluation of measurement methods;research on impact modeling and risk assessment of software requirements change based on dependency structure matrix;improved brain tumor segmentation framework based on multimodal MRI and cascaded segmentation strategy;probabilistic safety verification of stochastic hybrid systems using probably approximately correct barrier certificates;research on electricity price prediction technology based on mode decomposition and deep learning;and a local differential privacy preservation method for high-dimensional data based on big data mining.
Aiming at the intelligent substation transmission architecture there are wiring complexity, operation and maintenance inefficiency, this paper designs a new type of networking scheme to realize the mixed transmission ...
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