Range-Of-Motion
发表于 2025-3-23 12:31:46
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战胜
发表于 2025-3-23 16:59:38
Karlheinz Knapp Prof. Dr. propose a self-adaptive . solution with a built-in suboperator cost model that dynamically selects the best . strategy at runtime according to the data skew of the target query. We implement the solution in the commercial shared-nothing ., namely CockroachDB and empirical study justifies that the s
整洁
发表于 2025-3-23 20:03:38
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Congregate
发表于 2025-3-24 01:48:18
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barium-study
发表于 2025-3-24 04:29:27
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轻推
发表于 2025-3-24 09:48:17
Karlheinz Knapp Prof. Dr.e normal contact force between the rolling elements and the two bearing races are established, including the effects of raceway surface roughness. Various contact force models with different hysteresis damping formulations are examined in order to select the best suited for the application. The bear
constitute
发表于 2025-3-24 12:49:37
Karlheinz Knapp Prof. Dr. transactions, while maintaining strong concealment. This study focuses on utilizing blockchain transaction values as a carrier, exploring methods to ensure that the distribution of values with embedded data mimics that of standard transactions. Initially, we gathered authentic blockchain transactio
泰然自若
发表于 2025-3-24 17:01:41
Karlheinz Knapp Prof. Dr.nt of research. This paper introduces a vehicular network communication system based on cloud computing and blockchain technology, aimed at enhancing the efficiency and security of vehicle privacy protection and message authentication. The system architecture comprises five core components: the Traf
灾祸
发表于 2025-3-24 21:55:25
Karlheinz Knapp Prof. Dr.tation, built through collective feedback, impacts vendor trustworthiness and support. However, centralized systems like eBay and Amazon pose privacy concerns as users must trust the central server to maintain accurate records and protect sensitive data. Decentralized solutions offer greater privacy
Armory
发表于 2025-3-24 23:28:41
Karlheinz Knapp Prof. Dr.g is typically confined to pure graph learning tasks, such as node classification or link prediction. So far, graph prompt learning has been scarcely applied to recommender system, particularly in sequential recommendation. In this paper, we propose a pioneering approach, Graph Prompt for Session-ba