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Titlebook: Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health; International 2019 C Huansheng Ning Conference proceedings 2019 S

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41#
發(fā)表于 2025-3-28 16:45:11 | 只看該作者
42#
發(fā)表于 2025-3-28 19:57:56 | 只看該作者
Replicating Adenoviruses in Cancer Therapya and semi-structured data which are hard for machine-understanding and reuse. Security expert need to analyze the description, link to related knowledge and reason out the hidden connection among various weakness. It is necessary to analyze the vulnerability data automatically and manage knowledge
43#
發(fā)表于 2025-3-29 01:36:35 | 只看該作者
Evasion of the Immune System by Adenovirusesl greatly benefit the development of economics, and society. It is difficult to assess the management of knowledge. Principal component analysis has been used to the knowledge management with the economic data, population data, educational data, research data for two developing countries and two dev
44#
發(fā)表于 2025-3-29 07:09:29 | 只看該作者
45#
發(fā)表于 2025-3-29 08:18:18 | 只看該作者
46#
發(fā)表于 2025-3-29 15:02:03 | 只看該作者
https://doi.org/10.1007/978-3-662-05597-7 distance attribute but also the direction attribute. In this paper, we propose a new spatial object query, i.e., the direction-aware top-. dominating query (DirDom query). Given a user’s position and his favorite direction, the DirDom query finds the top-. objects with the highest dominant capabili
47#
發(fā)表于 2025-3-29 17:33:36 | 只看該作者
48#
發(fā)表于 2025-3-29 23:12:51 | 只看該作者
Mildred L. G. Shaw,Brian R. Gainest based on the combination of word embedding and semantic weight is low in computational complexity and its performance is even better than that based on complex structure such as RNN and LSTM. This paper proposes a semantic representation model of short text based on ELMO (Embeddings from Language
49#
發(fā)表于 2025-3-30 02:41:51 | 只看該作者
Mildred L. G. Shaw,Brian R. Gainesimbalanced data. This paper proposes a feature pattern-based LSTM method (called FLSTM, Feature based Long Short Term Memory) to analyze failures through processing imbalanced data. The method constructs a time-series feature matrix as the input to the LSTM model. In addition, we propose a failure p
50#
發(fā)表于 2025-3-30 06:50:15 | 只看該作者
Scott A. Davis,Steven R. Feldmanlationship can help us quickly screen and search for influential authors from a large number of authors, and then can be applied to author ranking, author recommendation and other systems. A method of building an author influence map is proposed in this paper. By introducing entropy weight method, e
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