IPv6协议一致性测试是保证IPv6协议实现正确性及有效性的方法。当前IPv6一致性测试系统共同的不足是标准协议的数量受限,并且对新型协议的支持不够。在这种需求的驱动下,提出一种可扩展模块化测试描述语言EMTL(Extensible Modular Test ...IPv6协议一致性测试是保证IPv6协议实现正确性及有效性的方法。当前IPv6一致性测试系统共同的不足是标准协议的数量受限,并且对新型协议的支持不够。在这种需求的驱动下,提出一种可扩展模块化测试描述语言EMTL(Extensible Modular Test Description Language),设计并开发了IPv6协议一致性测试系统,描述该系统各部件的具体功能。在对IPv6无状态地址自动分配协议的标准描述分析的基础上设计一套测试集,用IPv6协议一致性测试系统在Linux系统平台上对该协议进行测试,成功得到了相应测试结果,验证了该系统具有很好的测试能力和功能通用性。展开更多
In this investigation,we have shown that the combination of deep learning,including natural language processing,and conformal prediction results in highly predictive and efficient temporal test set sentiment estimates...In this investigation,we have shown that the combination of deep learning,including natural language processing,and conformal prediction results in highly predictive and efficient temporal test set sentiment estimates for 12 categories of Amazon product reviews using either in-category predictions,i.e.the model and the test set are from the same review category or cross-category predictions,i.e.using a model of another review category for predicting the test set.The similar results from in-and cross-category predictions indicate high degree of generalizability across product review categories.The investigation also shows that the combination of deep learning and conformal prediction gracefully handles class imbalances without explicit class balancing measures.展开更多
文摘IPv6协议一致性测试是保证IPv6协议实现正确性及有效性的方法。当前IPv6一致性测试系统共同的不足是标准协议的数量受限,并且对新型协议的支持不够。在这种需求的驱动下,提出一种可扩展模块化测试描述语言EMTL(Extensible Modular Test Description Language),设计并开发了IPv6协议一致性测试系统,描述该系统各部件的具体功能。在对IPv6无状态地址自动分配协议的标准描述分析的基础上设计一套测试集,用IPv6协议一致性测试系统在Linux系统平台上对该协议进行测试,成功得到了相应测试结果,验证了该系统具有很好的测试能力和功能通用性。
文摘In this investigation,we have shown that the combination of deep learning,including natural language processing,and conformal prediction results in highly predictive and efficient temporal test set sentiment estimates for 12 categories of Amazon product reviews using either in-category predictions,i.e.the model and the test set are from the same review category or cross-category predictions,i.e.using a model of another review category for predicting the test set.The similar results from in-and cross-category predictions indicate high degree of generalizability across product review categories.The investigation also shows that the combination of deep learning and conformal prediction gracefully handles class imbalances without explicit class balancing measures.
