Accurate fault diagnosis plays a key role in the safe and efficient operation of electrical motors. Aiming at multi-class motor fault diagnosis under complex working conditions, a signal fusion-based fault diagnosis f...
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Making hybrid systems more efficient and eco-friendlier by using Renewable energy resources is an inspiring idea. Two tourism different locations including Sarab Gyan in Iran and Zurich city in Switzerland are analyse...
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- Renewable resources are adopted nowadays to promote sustainable development, enhance energy security, and build resilient communities. The increase in demand for renewable resources has led to the use of photovoltai...
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In a digital system, the interleaver is essential. It's widely used to enhance the effectiveness of forward error correction codes. A lot of research has shown the efficiency of the chaotic interleaver in correcti...
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With a wide range of applications in autonomous driving and robotics,semantic seg-mentation for large‐scale outdoor point clouds is a critical and challenging *** to the large number and irregular arrangement of poin...
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With a wide range of applications in autonomous driving and robotics,semantic seg-mentation for large‐scale outdoor point clouds is a critical and challenging *** to the large number and irregular arrangement of point clouds,it is difficult to balance the efficiency and *** this paper,we propose LessNet,a lightweight and efficient voxel‐based method for LiDAR‐only semantic segmentation,taking advantage of cylin-drical partition and intra‐voxel feature ***,we use a cylindrical partition method to distribute the outdoor point clouds more evenly in *** better encode the voxel features,we adopt an intra‐voxel aggregation method without querying *** voxel features are further input into a lightweight and effective 3D U‐net to aggregate local features and dilate the receptive *** experiments prove the satisfied semantic segmentation performance and the improvement of each component in our proposed *** method is capable of processing more than one million point clouds at a time while retaining low latency and few ***,our method achieves comparable performance with state‐of‐the‐art approaches and out-performs all projection‐based methods on the SemanticKITTI benchmark.
The paper proposes a game, EverydayFantasy, based on the principles of serious games, game mechanics and gamification and intended for young people with cognitive behavior issues. The game is a mobile computing applic...
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One of the most important goals of theoretical ecologists is to find a strategy for controlling the chaos in ecological models to maintain healthy ecosystems. We investigate the influence of fear and the supply of add...
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We consider the problem of control allocation for weakly redundant systems subject to actuator faults. In particular, the design of a suitable allocator will be devised with the aim of compensating for the fault effec...
In this study, we introduce a novel auction-based algorithm modeled as a decentralized coalition formation game, designed for the complex requirements of large-scale multi-robot task allocation under uncertain demand....
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In this study, we introduce a novel auction-based algorithm modeled as a decentralized coalition formation game, designed for the complex requirements of large-scale multi-robot task allocation under uncertain demand. This context is particularly illustrative in scenarios where robots are tasked to charge electric vehicles. The algorithm begins by partitioning a composite task sequence into distinct subsets based on spatial similarity principles. Subsequently, we employ a coalition formation game paradigm to coordinate the assembly of robots into cooperative coalitions focused on these distinct subsets. To mitigate the impact of unpredictable task demands on allocations, our approach utilizes the conditional value-at-risk to assess the risk associated with task execution, along with computing the potential revenue of the coalition with an emphasis on risk-related outcomes. Additionally, integrating consensus auctions into the coalition formation framework allows our approach to accommodate assignments for individual robot-task pairings, thus preserving the stability of individual robotic decision autonomy within the coalition structure and assignment distribution. Simulative analyses on a prototypical parking facility layout confirm that our algorithm achieves Nash equilibrium within the coalition structure in polynomial time and demonstrates significant scalability. Compared to competing algorithms, our proposal exhibits superior performance in resilience, task execution efficiency, and reduced overall task completion times. The results demonstrate that our approach is an effective strategy for solving the scheduling challenges encountered by multi-robot systems operating in complex environments. IEEE
This paper presents a study on the performance of different windowing techniques for high-level quadrature amplitude modulation (QAM) in universal filtered multicarrier (UFMC) systems. The focus is on comparing the im...
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