This work presents the development of an algorithm for automated abstract generation of scientific publications that integrates the capabilities of ChatGPT with expertise in the field of academic writing. The developm...
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This paper presents the WDCLF (Web Declare, Conceptual, Logical, Physical) method for web database design (WDB), which has been adapted to the needs of web applications. The WDCLF extends traditional database design a...
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Timetabling is essential for the organization and functioning of higher education institutions (HEIs). This complex task requires balancing various factors such as availability of teachers, availability of halls, huge...
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Unlike teaching theoretical subjects, teaching practical subjects have differences and require some special considerations. In a higher education institution (HEI) with a technical focus, learning practical skills is ...
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Online examination of engineering students is a complex and multi-layered process that requires careful planning and integration of various technologies. Engineering disciplines are characterized by high demands on st...
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Artificial intelligence (AI) is becoming increasingly important in the field of scientific research, providing new opportunities for processing large amounts of data, automating routine tasks, and discovering new depe...
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This paper focuses on the optimal output synchronization control problem of heterogeneous multiagent systems(HMASs) subject to nonidentical communication delays by a reinforcement learning *** with existing studies as...
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This paper focuses on the optimal output synchronization control problem of heterogeneous multiagent systems(HMASs) subject to nonidentical communication delays by a reinforcement learning *** with existing studies assuming that the precise model of the leader is globally or distributively accessible to all or some of the followers, the leader's precise dynamical model is entirely inaccessible to all the followers in this paper. A data-based learning algorithm is first proposed to reconstruct the leader's unknown system matrix online. A distributed predictor subject to communication delays is further devised to estimate the leader's state, where interaction delays are allowed to be nonidentical. Then, a learning-based local controller, together with a discounted performance function, is projected to reach the optimal output synchronization. Bellman equations and game algebraic Riccati equations are constructed to learn the optimal solution by developing a model-based reinforcement learning(RL) algorithm online without solving regulator equations, which is followed by a model-free off-policy RL algorithm to relax the requirement of all agents' dynamics faced by the model-based RL algorithm. The optimal tracking control of HMASs subject to unknown leader dynamics and communication delays is shown to be solvable under the proposed RL algorithms. Finally, the effectiveness of theoretical analysis is verified by numerical simulations.
Intelligent vehicles and autonomous driving systems rely on scenario engineering for intelligence and index (I&I), calibration and certification (C&C), and verification and validation (V&V). To extract and...
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Intelligent vehicles and autonomous driving systems rely on scenario engineering for intelligence and index (I&I), calibration and certification (C&C), and verification and validation (V&V). To extract and index scenarios, various vehicle interactions are worthy of much attention, and deserve refined descriptions and labels. However, existing methods cannot cope well with the problem of scenario classification and labeling with vehicle interactions as the core. In this paper, we propose VistaScenario framework to conduct interaction scenario engineering for vehicles with intelligent systems for transport automation. Based on the summarized basic types of vehicle interactions, we slice scenario data stream into a series of segments via spatiotemporal scenario evolution tree. We also propose the scenario metric Graph-DTW based on Graph Computation Tree and Dynamic Time Warping to conduct refined scenario comparison and labeling. The extreme interaction scenarios and corner cases can be efficiently filtered and extracted. Moreover, with naturalistic scenario datasets, testing examples on trajectory prediction model demonstrate the effectiveness and advantages of our framework. VistaScenario can provide solid support for the usage and indexing of scenario data, further promote the development of intelligent vehicles and transport automation. IEEE
For a large energy storage is necessary to balance energy between cells to extend battery resource and storage capacity. During cell balancing energy dissipation is unavoidable. Three main solutions are existing to de...
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The results of research in the field of development of multi-aspect geographical information models for digital twins of spatially distributed objects are presented. It is shown that digital twins of spatial objects, ...
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