DV-Hop中虫洞攻击的仿真及其抵抗方法

APS(Ad Hoc Position System)中的DV-Hop算法因其良好的精度及与测距误差无关等特点而使之为一个优秀的算法。但其安全性比较差,容易受到攻击。虫洞攻击是一种容易实现且破坏性大的攻击。DV-Hop算法依靠距离矢量交换估计距离,容易受到虫洞攻击的影响。提出在DV-Hop算法中增加检测虫洞攻击及抵抗该攻击的方法,并通过Algosensim仿真软件进行模拟。通过实验表明,修改后的DV-Hop算法对于虫洞攻击有较好的抵抗性。

A multi-attention RNN-based relation linking approach for question answering over knowledge base

Aiming at the relation linking task for question answering over knowledge base,especially the multi relation linking task for complex questions,a relation linking approach based on the multi-attention recurrent neural network(RNN)model is proposed,which works for both simple and complex questions.First,the vector representations of questions are learned by the bidirectional long short-term memory(Bi-LSTM)model at the word and character levels,and named entities in questions are labeled by the conditional random field(CRF)model.Candidate entities are generated based on a dictionary,the disambiguation of candidate entities is realized based on predefined rules,and named entities mentioned in questions are linked to entities in knowledge base.Next,questions are classified into simple or complex questions by the machine learning method.Starting from the identified entities,for simple questions,one-hop relations are collected in the knowledge base as candidate relations;for complex questions,two-hop relations are collected as candidates.Finally,the multi-attention Bi-LSTM model is used to encode questions and candidate relations,compare their similarity,and return the candidate relation with the highest similarity as the result of relation linking.It is worth noting that the Bi-LSTM model with one attentions is adopted for simple questions,and the Bi-LSTM model with two attentions is adopted for complex questions.The experimental results show that,based on the effective entity linking method,the Bi-LSTM model with the attention mechanism improves the relation linking effectiveness of both simple and complex questions,which outperforms the existing relation linking methods based on graph algorithm or linguistics understanding.

Revision of stratified OWL ontologiesbased on integer linear programming

To revise stratified web ontology language(OWL)ontologies,the kernel revision operator is extended by defining novel conflict stratification and the incision function based on integer linear programming(ILP).The ILP-based model considers an optimization problem of minimizing a linear objective function which is suitable for selecting the minimal number of axioms to remove when revising ontologies.Based on the incision function,a revision algorithm is proposed to apply ILP to all minimal incoherence-preserving subsets(MIPS).Although this algorithm can often find a minimal number of axioms to remove,it is very time-consuming to compute MIPS.Thus,an adapted revision algorithm to deal with unsatisfiable concepts individually is also given.Experimental results reveal that the proposed ILP-based revision algorithm is much more efficient than the commonly used algorithm based on the hitting set tree.In addition,the adapted algorithm can achieve higher efficiency,while it may delete more axioms.

Hierarchical annotation method for metal corrosion detection of power equipment

To solve the ambiguity and uncertainty in the labeling process of power equipment corrosion datasets,a novel hierarchical annotation method(HAM)is proposed.Firstly,large boxes are used to label a large area covering the range of corrosion,provided that the area is visually continuous and adjacent to corrosion that cannot be clearly divided.Secondly,in each labeling box established in the first step,regions with distinct corrosion and relative independence are labeled to form a second layer of nested boxes.Finally,a series of comparative experiments are conducted with other common annotation methods to validate the effectiveness of HAM.The experimental results show that,with the help of HAM,the recall of YOLOv5 increases from 50.79%to 59.41%;the recall of Faster R-CNN+VGG16 increases from 66.50%to 78.94%;the recall of Faster R-CNN+Res101 increases from 78.32%to 84.61%.Therefore,HAM can effectively improve the detection ability of mainstream models in detecting metal corrosion.

移动IPv6技术研究

随着移动IP的发展和应用，最初的移动IPv4已经暴露出先天不足。由于移动IPv4的缺陷（如三角路由问题），移动IPv6的设计借鉴了开发移动IPv4的经验，并且利用了IPv6提供的新特性。移动IPv6正在成为IP不可缺少的部分。而且比移动IPv4有很多显著的改进。通过对其工作原理和基于移动IPv4存在的问题进行了分析，比较了移动IPv6和移动IPv4的差异，介绍了移动IPv6的主要工作过程。移动IPv6的真正推广，一方面需要借助下一代网络的快速发展需求，另一方面也需要克服目前存在的一些问题。