Multimodal magnetic resonance imaging for Alzheimer's disease diagnosis using hybrid features extraction and ensemble support vector machines

Magnetic resonance imaging (MRI) is increasingly used in the diagnosis of Alzheimer's disease (AD) in order to identify abnormalities in the brain. Indeed, cortical atrophy, a powerful biomarker for AD, can be detected using structural MRI (sMRI), but it cannot detect impairment in the integrity of the white matter (WM) preceding cortical atrophy. The early detection of these changes is made possible by the novel MRI modality known as diffusion tensor imaging (DTI). In this study, we integrate DTI and sMRI as complementary imaging modalities for the early detection of AD in order to create an effective computer-assisted diagnosis tool. The fused Bag-of-Features (BoF) with Speeded-Up Robust Features (SURF) and modified AlexNet convolutional neural network (CNN) are utilized to extract local and deep features. This is applied to DTI scalar metrics (fractional anisotropy and diffusivity metric) and segmented gray matter images from T1-weighted MRI images. Then, the classification of local unimodal and deep multimodal features is first performed using support vector machine (SVM) classifiers. Then, the majority voting technique is adopted to predict the final decision from the ensemble SVMs. The study is directed toward the classification of AD versus mild cognitive impairment (MCI) versus cognitively normal (CN) subjects. Our proposed method achieved an accuracy of 98.42% and demonstrated the robustness of multimodality imaging fusion.     

基于Harn部分盲签名的安全电子投票方案

本文设计了一种新的Harn部分盲签名方案,并将此方案用于电子投票的设计中,形成了一个安全可靠的电子投票方案。这种电子投票方案不仅保证了投票者身份的匿名性和选票的安全、公平、保密性,还能实现投票的不可抵赖性。此方案是传统的盲签名电子投票方案的一个改进,是一个很实用的方案。     

用于WSN中结点认证协议的投票机制

研究并设计一种超半数“投票”方案。以簇头为计票者,认证结点为投票者,由簇头搜集与统计“选票”信息。依据超半数投票原则得出统计结果,断定可疑结点的真实性。通过理论推导和计算证明,在异构的传感网络中,投票统计结果的可信度达90%以上,能够准确、可靠地检测出可疑结点,提高无线传感器网络的安全。     

Feature detection of triangular meshes based on tensor voting theory

This paper presents n-dimensional feature recognition of triangular meshes that can handle both geometric properties and additional attributes such as color information of a physical object. Our method is based on a tensor voting technique for classifying features and integrates a clustering and region growing methodology for segmenting a mesh into sub-patches. We classify a feature into a corner, a sharp edge and a face. Then, finally we detect features via region merging and cleaning processes. Our feature detection shows good performance with efficiency for various dimensional models.     

Effective solution for unhandled exception in decision tree induction algorithms

This paper deals with some improvements to rule induction algorithms in order to resolve the tie that appear in special cases during the rule generation procedure for specific training data sets. These improvements are demonstrated by experimental results on various data sets. The tie occurs in decision tree induction algorithm when the class prediction at a leaf node cannot be determined by majority voting. When there is a conflict in the leaf node, we need to find the source and the solution to the problem. In this paper, we propose to calculate the Influence factor for each attribute and an update procedure to the decision tree has been suggested to deal with the problem and provide subsequent rectification steps.     

New receipt-free voting scheme using double-trapdoor commitment

It is considered to be the most suitable solution for large scale elections to design an electronic voting scheme using blind signatures and anonymous channels. Based on this framework, Okamoto first proposed a receipt-free voting scheme [30] for large scale elections. However, in the following paper, Okamoto [31] proved that the scheme [30] was not receipt-free and presented two improved schemes. One scheme requires the help of the parameter registration committee and the other needs a stronger physical assumption of the voting booth. In this paper, we utilize the double-trapdoor commitment to propose a new receipt-free voting scheme based on blind signatures for large scale elections. Neither the parameter registration committee nor the voting booth is required in our scheme. We also present a more efficient zero-knowledge proof for secret permutation. Therefore, our scheme is much more efficient than Okamoto’s schemes [30] and [31] with the weaker physical assumptions. Moreover, we prove that our scheme can achieve the desired security properties.     

强盲签名技术的研究与应用

根据近年来国内外关于数字签名的研究背景及进展,阐述盲签名在计算机保密通信,特别是在电子货币等方面的一系列重要应用。最后指出了若干有待继续研究的课题。     

Ranking alternatives in a preferential voting system using fuzzy concepts and data envelopment analysis

In this paper, a new method for aggregating the opinions of experts in a preferential voting system is proposed. The method, which uses fuzzy concept in handling crisp data, is computationally efficient and is able to completely rank the alternatives. Through this method, the number of votes for certain rank position that each alternative receives are first grouped together to form fuzzy numbers. The nearest point to a fuzzy number concept is then used to introduce an artificial ideal alternative. Data envelopment analysis is next used to find the efficiency scores of the alternatives in a pair-wise comparison with the artificial ideal alternative. Alternatives are rank based on these efficiency scores. If the alternatives are not completely ranked, a weight restriction method also based on fuzzy concept is used on the un-discriminated alternatives until they are completely ranked. Two examples are given for illustration of the method.     

多个大股东并存下的公司治理研究综述

在不同国家的企业中股权结构有很大差异.多个大股东并存下的股权制衡模式作为一种特殊的股权结构,产生了其特有的公司治理问题.文中主要从多个大股东并存的公司治理效应、对于公司决策和业绩的影响、与公司价值的关系三个方面对国外研究进行了综述,较为全面的总结了前人对于多个大股东并存下的股权制衡的公司治理问题的研究.     

公钥密码体制的同态性分析

同态加密算法是基于秘密同态的概念,是秘密同态的一个子集。同态加密技术可以对加密数据直接进行运算,并且运算结果也自动加密。正是基于此,使得同态加密技术在安全多方计算、数据库加密、电子投票等领域具有广泛的应用。同态特性主要包括加法特性、乘法特性、混合乘法特性。文章对目前广泛应用的三大公钥密码体制的同态特性进行了分析,并对满足加法同态的Pallier密码体制进行了研究。为后续研究全同态加密算法提供理论基础和方法指导。