Improved Authenticated Multi-Key Agreement Protocol

Zhou et al give an attack on Ham＇s modified authenticated multi-key agreement protocol, and give a protocol that can prevent the unknown key-share attack. The paper points out that the protocol is vulnerable to a concatenation attack. This paper proposes an improved authenticated multi-key agreement protocol which shows how to make Harn＇s protocol more secure by modifying the signature and verification. And this protocol can escape the concatenation attack.     

面向大语料库的语音合成方法研究

针对几百小时粗标注大语料库, 提出一种新颖的语音合成系统构建方法。首先, 借助于语音识别、文本对齐和句法分析等技术实现大语料库的自动筛选与标注。 然后, 为了有效解决大语料库声学模型训练中存在的内存空间以及计算时间开销过大等问题, 优化了传统的训练流程, 在不损失声学模型准确性的前提下, 显著提高了模型的训练速度。主观实验表明, 与具有精标注的小语料库相比, 引入粗标注的大语料库可以带来0.5分左右的MOS提升。     

基于可变长音素序列拼接单元的维吾尔语语音合成技术研究

文章采用了一种以可变长音素序列为拼接单元的维吾尔语语音合成系统的技术方案,阐述了维吾尔语的语言特点及语音合成中必须考虑的语音协同发音等现象,给出了语音库的设计思路及其句子、短语、词语、音节以及音素等多级语音库结构,以便直接从语音库中找到拼接单元,还考虑了怎样合成语音库中没有拼接单元的情况。该方法能更好地利用自然语流的原始信息,提升了系统合成语音效果的自然度。     

地下连续墙工程的组价方法

根据深圳地铁福民站地下连续墙工程实例，结合其施工工艺，分析地下连续墙工程合理的人工、材料、施工机械以及管理费等各项费用的组成，研究其合理的组价方法。     

正交Bent函数组与高非线性度满足SAC平衡函数

通过构造一组正交的Bent函数(序列),利用它进一步构造出一类具有高非线性度、满足SAC的平衡函数,得到比较广泛的结果。     

Algebraic characterization of RNA operations for DNA-based computation

Any RNA strand can be presented by a word in the language X*, where X={A,C,G,U}. By encoding A as 010, C as 000, G as 111, and U as 101, the RNA operations can be considered as the performance of concatenation, union, reverse, complement, in terms of the algebraic characterization. The concatenation and union play the roles of multiplication and addition over some algebraic structures, respectively. The rest of the operations turn out to be the homomorphisms or anti-homomorphisms of these algebraic structures. Using this technique, we find the relationship among these RNA operations.     

Algebraic characterization of RNA operations for DNA-based computation

In 1994 ,AldemansuccessfullyintroducedDNA basedcomputingasanapproachtosolvingmathemat icalproblems[1] ,whichusesDNAasadatacarrierandtechniquesofmolecularbiologytooperateonDNA .FollowingAdleman ,DNAalgorithmshavebeenfoundtosolveother problems :expansionofsymbolicdeterminants[2 ] ,matrixmultiplication[3] ,addition[4 ] ,exascalecomputeralgebra[5] ,andsoon .Liptonetal.introducedanewmethodforcon structionofbinarynucleicacidlibraries[6 ] ,andtheyintroducedRNAasamoleculeforcomputationtopre sent…     

Trainable unit selection speech synthesis under statistical framework

This paper proposes a trainable unit selection speech synthesis method based on statistical modeling framework. At training stage, acoustic features are extracted from the training database and statistical models are estimated for each feature. During synthesis, the optimal candidate unit sequence is searched out from the database following the maximum likelihood criterion derived from the trained models. Finally, the waveforms of the optimal candidate units are concatenated to produce synthetic speech. Experiment results show that this method can improve the automation of system construction and naturalness of synthetic speech effectively compared with the conventional unit selection synthe- sis method. Furthermore, this paper presents a minimum unit selection error model training criterion according to the characteristics of unit selection speech synthesis and adopts discriminative training for model parameter estimation. This criterion can finally achieve the full automation of system con- struction and improve the naturalness of synthetic speech further.     

一类Bent序列的构造方法

通过构造一类称之为M-型的矩阵,证明按行下标非退化线性变换的次序级联M-型矩阵的行所得的序列是Bent序列,从而得到了一批Bent函数,推广了R.Yarlardda的结果。